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Chapter 1 - Introduction
1.1 International Trade
The exchange of goods and services between countries is referred to as international
trade (Schulze, 1999). It establishes a global economy where supply and demand have
a significant influence on the development of countries. Industrialization of economies
is significantly influenced by trade (Krugman & Obstfeld, 2021). Trade enables
countries to widen their markets, increase their income, and accelerate economic
growth. However, depending on the degree of development in each country as well as
global events, the effects of international trade on the economy might vary
significantly from one country to another.
Measuring economic growth can be complex but the role of international trade in
fostering economic growth has become increasingly prominent (Kaplinsky, 2005). The
connection between neoclassical growth and international commerce may be most
effectively elucidated through David Ricardo's idea of comparative advantage.
According to this theory, countries are advised to manufacture items with lower
opportunity costs compared to other countries. This phenomenon took place within the
framework of the neoclassical trade regime, which posits that nations may enhance
their Gross Domestic Product (GDP) by leveraging changes in capital and labour,
facilitated by the adoption of technological advancements (Krueger, 1985). The World
Trade Organization (2020) defines international trade as a transaction that occurs
across borders and results in the flow of goods and services between nations. Maritime
transport is a critical and inevitable component of international trade as 70% of global
trade value and about 80% of global trade volume is transported by sea primarily
because maritime transportation is cheap and can move large amounts of cargo across
long distances to diverse destinations (UNCTAD, 2020).
Internationally traded commodities may often be split into two categories namely hard
and soft commodities. Natural resources like gold and oil are examples of hard
commodities. These resources are mined or exploited from their natural sites.
Contrarily, soft commodities are agricultural goods or livestock such as coffee or cattle
(CFI Team, 2019). According to value and volume, the top commodities traded
internationally on a global scale are hydrocarbon Commodities (Oil and Natural Gas)
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also referred to as energy commodities, Agricultural goods (coffee, wheat, cotton), and
animal and animal products. (Thaxton, 2022). Metals (gold, silver, copper), and
minerals (coal, iron ore) are also examples of internationally traded commodities.
However, both industrial production, local consumption, or international trade of these
commodities have implications for the economic development of trading nations. The
GDP of a nation is used to measure its economic development (United Nations, n.d.),
and the global economy may be significantly impacted by trade of commodities.
Revenues are generated from exports and imports of commodities. When demand and
prices are high globally, countries that export many goods may see significant gains in
GDP (Hufbauer, 1970). Revenue from exports can be used in infrastructure and
economic expansion. On the other hand, nations that rely significantly on commodity
imports could experience financial difficulties as prices increase, which would hurt
their GDP. A country's GDP may benefit when its terms of trade improve because it
will have greater buying power for imported items when export prices increase in
relation to import prices (Wong, 2009). Globally, while the volume of commodities
used has increased significantly due to population growth and wider income, their
relative importance has changed through time as a result of technical advancements
that have given birth to new applications for some materials and made it easier for
commodities to be substituted (Baffes & Nagle, 2022). The International Trade of a
nation is heavily influenced by commodities, particularly in economies that are heavily
dependent on these commodities, thus, contributing to foreign direct investment (FDI)
and promoting economic growth. For instance, countries with significant mineral
resources could experience a surge in FDI for mining and related businesses, resulting
in the creation of jobs the expansion of infrastructure, and overall improvements in the
economy (Mottaleb & Kalirajan, 2010).
1.2 International Commodities Trade
The energy industry covers a diverse array of commodities that are utilized for the
purposes of power generation, heating, and transportation (Speight, 2018). According
to Chan, (2020) report on the most traded commodity globally, Brent Crude oil is
number 1, followed by coffee and Natural Gas at number 3. Thus international energy
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trade is vital. Energy trading involves products like crude oil, electricity, natural gas,
and wind power and trading in these commodities comes with a lot of fluctuations
(Federal Energy Regulatory Commission, 2020). Energy is divided into two types
Renewable and non-renewable. Fossil fuels account for 63% of global electricity
(Ritchie & Roser, 2022). The term "Energy Commodities" refers to electricity, Green
Power, natural gas, methane, and any other petroleum-based fuel products such as
diesel, bio-diesel, unleaded, fuel oil, and propane (Vacha & Barunik, 2012). However,
it is important to note that the energy sector is expansive and always expanding, as
novel technology and resources continue to emerge. The world's Trade in goods is
significantly influenced by primary commodities. Although industrialised nations
dominate primary commodity trade, the LDCs are far more dependent on it for their
national income, export revenues, and jobs (T. Ademola Oyejide, 1989). Due to this
dependency, the LDCs face serious issues with several major commodity trade features.
Primary commodity export-dependent nations frequently experience decreases in their
terms of trade; the volatility of primary commodity prices and export revenues adds to
the difficulties. Crude oil has been one of the most important commodities in the 20th
and 21st centuries, significantly due to the influence and importance it has on
industrialization. Crude oil is a major energy source for the production of power, heat,
and transportation (CAPP, 2019). Petroleum-based products were crucial to the
development of internal combustion engines and the expansion of the car industry (Seo,
2016). Because of its dependence on oil, modern lives and economic activities are
largely driven by it compared to other commodities.
1.2.1 Crude Oil
Crude oil is a natural resource composed of hydrocarbon deposits and other organic
matter that is found in nature and serves as a primary source of petroleum (Daniel
Liberto, 2023). Its widespread usage in manufacturing, transportation, and many other
economic areas serves as evidence of its significance. It is traded both as spot oil or
contract derivatives with over a billion Dollars traded daily (Adi Imsirovic, 2022).
Geopolitical developments, dynamics of supply and demand, and actions made by
major oil-producing nations may all affect its pricing. The economic and plentiful
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supply of crude oil has been a key driver of industrialization. It is highly sought after
on a global scale and is actively traded on futures markets such as the New York
Mercantile Exchange (NYMEX). Upon undergoing the process of refinement, crude
oil can yield several valuable products, including but not limited to petrol, diesel, and
jet fuel (U.S. Energy Information Administration, 2022). Crude oil is refined into
petroleum products, also used to make polymers, chemicals, synthetic materials, and
other goods in addition to being utilised as a fuel. (Energy Information Administration,
2016) Because they rely on oil-derived inputs, industries like petrochemicals, plastics,
and manufacturing have prospered.
1.2.2. Natural Gas
As the world moves towards cleaner energy sources (Singh et al., 2021), natural gas
demand has been rising as a bridge fuel from fossil to renewable energy sources (Birol,
2019). It is a type of fossil fuel that is predominantly composed of methane, used in
electricity generation, heating, and as a source of fuel for cars (Birol, 2019). Crude oil
reserves frequently coexist with natural gas deposits. Liquefied natural gas (LNG),
which enables simpler transportation over long distances and access to markets that
were previously inaccessible by pipelines, has contributed to natural gas' rise to
prominence as an important commodity in international commerce (Cattlin, 2021).
This is particularly true given the emergence of LNG. Several nations have increased
the amount of LNG they import to broaden their variety of energy sources, enhance
their energy security, and move to fuels that produce less pollution (IEA, 2022).
According to the International Energy Agency by 2030, global electricity demand for
electric vehicles will increase five- to eleven-fold more than the demand in 2019 (IEA,
2020). The worldwide commerce of gas has ramifications for geopolitics, and it
frequently affects the relationships between different nations. The use of futures
contracts, such as the Henry Hub natural gas futures contract offered by the CME, is
the method that is most frequently utilised by traders to take a position on natural gas.
Traders agree, as part of a futures contract, to take delivery of a predetermined quantity
of natural gas at a predetermined date in the future at a price that has been
predetermined. Policies about energy can have repercussions on many continents due
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to the increased interconnection of nations brought about by the development of gas
infrastructure (U.S. Energy Information Administration, 2016).
1.2.3. Coal
Coal is classified as a fossil fuel, derived from the organic matter of ancient plants that
underwent decomposition over millions of years. It is a sedimentary rock with a black
or brownish-black coloration, and is predominantly utilised to generate power. Despite
experiencing a decrease in utilisation in certain regions as a result of growing
environmental apprehensions, it continues to be a significant worldwide energy
provider (U S Energy Information Administration, 2016).
1.2.4. Uranium
Although uranium is not often regarded as a conventional commodity, it serves as the
principal fuel source for nuclear energy. Nuclear reactors employ uranium rods as a
means of generating electrical energy. Biofuels, which are obtained from biological
matter, have the potential to serve as viable alternatives to conventional petrol and
diesel fuels (US Energy Information Administration, 2016).
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1.3 International Crude Oil Trade and Energy Mix
Figure 1: 2021 World Crude Oil Trade
Source: The Observatory of Economic Complexity, 2021
The global trade of crude oil and Natural Gas products is extensive. There are not all
that many commercial ties between the nations. A global pattern of international trade
is formed by the tight or loose ties that certain nations have with other nations. The
worldwide commerce network is clustering into communities (or groupings) based on
criteria like geography or GDP rather than using regional trade agreements (Zhang et
al., 2018). For the benefit of policymakers, it is crucial to statistically demonstrate the
global pattern. Since the 20th century, oil and Gas have dominated the world's energy
use. The number of nations engaging in the global oil trade as well as the volume of
commerce have increased significantly, along with the glaring disparity in the
distribution of oil resources, (Zhang et al., 2015). However, the global oil trade patterns
have had a difficult evolution from the beginning of the oil trade, from their initial
bilateral patterns to their present multilateral patterns. Thus, the main supply regions
are the Middle East, Africa, and the former Soviet Union, whereas the primary demand
regions are North America, Europe, and the Asia-Pacific region, (Garlaschelli &
Loffredo, 2005).
Two-thirds of the price of oil in the world is based on Brent Crude, which is derived
from the North Sea, and has been the most traded commodity in the world for several
World
Trade
$951B
Top Exporter:
Saudi Arabia
$138B
Share of world
Trade
4.52
%
Top Importer
China
$208B
Export Growth
2020
-
2021
47.4
%
7
years. Brent Crude is mostly refined into diesel and petrol which are mostly used to
power combustion engines. On the other hand, WTI (West Texas Intermediary) is
sourced from the United States. WTI has less sulfur than Brent Crude, the second major
oil standard, and it is lighter, sweeter, and more refined. The easier and less expensive
it is to refine crude oil, the lower its sulfur concentration. Recent WTI oil production
has grown recently due to Fracking (Thaxton, 2022). However, Brent Crude has a
greater impact than WTI due to its proximity to Europe, Africa, and Asia. WTI crude
oil costs a little less than Brent crude, on average. The Brent/WTI spread, or price
differential, fluctuates frequently due to disparate supply sources. Global disputes in
Europe and the Middle East are more likely to have an impact on Brent Crude oil prices,
but WTI prices are more significantly impacted by political or economic events in the
US economy. Oil contracts for Brent Crude measure 1,000 barrels and are mostly traded
on the Intercontinental Exchange (ICE).
The economies of all countries are significantly impacted by the trade in crude oil and
Natural Gases (Alekhina & Yoshino, 2018). These effects can differ dramatically
depending on whether a nation exports or imports crude oil. The gross domestic
product (GDP) of countries that export oil is heavily influenced by oil sales earnings
(Hutt, 2016). In 2020, 70% of the national incomes of OPEC nations were generated
from oil exports. With large spending abilities. These nations grow their economies by
supporting various Sectors and industries such as infrastructure, manufacturing, health
care, and education (OPEC, 2021) while building safety nets during financial crises by
buffing up foreign reserves (Van der Ploeg, 2011).
Relying on oil exports comes with several concerns, including unstable earnings owing
to shifting oil prices globally. According to the "resource curse" or "paradox of plenty,"
countries with abundant natural resources like oil suffer less economic growth, weaker
democracy, and inferior development outcomes (Auty, 1993). On the other hand,
nations that often import oil experience the reverse result. They are vulnerable to
variations in the price of oil since it frequently makes up a sizable portion of their
energy mix. Inflation, a slowdown in economic development, and a worsened trade
balance can all result from price increases (Hamilton, 2011). High-income economies
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such as Germany and Japan over the years, have been able to maintain a robust
economy even though they are heavily dependent on oil importation. To achieve such
an economy, tactics such as energy efficiency, source diversification, and the creation
of alternative and renewable energy technologies are utilised (IEA, 2020). The oil
embargo of 1973 caused a severe recession in oil-importing nations, however, not all
countries that import oil suffer from these effects (US EIA, 2021). Both oilexporting
and oil-importing countries' economic conditions are significantly influenced by the
global trade of energy. Depending on several variables, such as price stability,
economic diversification, and energy policy, (which may be either advantageous or
detrimental), trade in crude oil may influence the economic prospects of nations.
Nations with considerable crude oil reserves frequently see major economic gains. Oil
exporting nations may generate sizable earnings, resulting in the expansion of their
infrastructure, investments in other industries, and GDP growth. However, these
economies may also be susceptible to changes in the price of oil, which might affect
their capacity to remain stable.
Furthermore, Relationships and conflicts in the world today are determined by who
has access to and control over crude oil/ Natural Gas resources. There have
occasionally been tensions and wars between states as a result of the search for oil
resources and geopolitical dynamics. Thus, geopolitical tensions and global
uncertainties could seriously affect energy trade and may alter the economic trajectory
of nations.
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Figure 2:Changes in the Global Energy Mix 2020-2040
Source: Canadian Association of Petroleum Producers (2019)
Figure 3: Projected World Energy Consumption in USD Source:
Canadian Association of Petroleum Producers, 2019
An increase in population and energy demand has a positive correlation, i.e. an
increase in population reflects a direct increase in energy demand. It will also lead to
a higher demand for petrochemicals used in transportation (The Canadian Association
of Petroleum Producers, 2019). However continuous improvements in energy
efficiency help reduce energy usage and demand. Natural Gas has become a popular
option as it is affordable and reliable with less emission compared to coal. By 2050
renewable energy would be 63% of the total primary energy supply (Gielen et al.,
2019).
2022
Billion
8
2030
8.5
Billion
2050
9.7
Billion
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1.4 International Energy Trade (Crude Oil & Natural Gas Trade) in Normal
Times and in Crises Times
Exports play a crucial role in the economy by enabling the efficient allocation of scarce
resources for the production of commodities and services. Additionally, the surplus of
exports can be traded to foreign markets to meet their needs, thereby increasing
national output and generating foreign exchange earnings. These revenues can then be
utilised to fund and promote initiatives for economic growth (Lal, 1992). On the other
hand, nations import crude oil and natural gas to satisfy their domestic energy demand.
They do this by increasing the variety of sources from which energy may be obtained,
hence decreasing reliance on any one particular source (EIA, 2018). When compared
to home production, the cost of acquiring goods or services from another nation may
be lower, making imports an attractive alternative. In addition, participation in
international trade helps nations improve their diplomatic and economic relations with
one another, which in turn makes participation in geopolitical cooperation easier.
Countries that are net importers of energy often have the necessary infrastructure, such
as refineries and processing facilities, to turn raw oil and natural gas into goods that
can be used, thereby adding value and supporting domestic companies to greater
productivity and national economic development (Di Bella et al., 2022). Thus, both
importing energy to add value locally or for resale at a favourable international price
are all dimensions of energy trade that nations could exploit for their economic
progress, based on their comparative advantages.
The global economy depends heavily on the trade of crude oil, although its trading is
quite complex and extremely susceptible to both macroeconomic and geopolitical
influences impacting everything from transportation to manufacturing. Normal
economic times and crisis events like wars, calamities, or pandemics have quite
different dynamics. Crises reveal the brittleness and complexity of the world oil
market, but normal times permit stability and predictability in the trade of this crucial
commodity. As nations negotiate the opportunities and difficulties of the world's
energy markets, governments, corporations, and international organisations must
understand these dynamics.
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1.4.1 Energy Trade in Normal Times
The worldwide crude oil trade is regulated throughout ordinary economic periods by
well-established customs, open market forces, and complex agreements. Crude oil
production and demand are often quite predictable. Major oil-producing nations
modify the output to suit global demand, frequently in concert with OPEC. Seasonal
fluctuations can be found in consumption habits, which are generally steady. The
nature of international economic interactions is frequently characterised by long-term
agreements and strategic partnerships. Pricing mechanisms are open, often enacted by
commodity exchanges like the NYMEX and Brent, and they take into account things
like transportation expenses, production costs, and market sentiment. To further ensure
the steady flow of oil and gas, countries often invest in infrastructures, such as
refineries, pipelines, and shipping facilities. This calls for both financial resources and
technical innovation to boost sustainability and efficiency (Cronshaw, 2015).
International agreements regulate commerce and guarantee conformity to international
norms for the preservation of the environment, safety, and morality. Also, natural gas
is directed by long-term contracts, the dynamics of demand and supply, and
considerations of the geopolitical environment. Natural gas is exported from nations
that have an abundance of reserves, such as Russia, the United States, and Qatar, to
nations that have a strong demand for the commodity, such as those in Europe or Asia
(Geng et al., 2014). Pipelines are often used to transport natural gas from one location
to another, while liquefied natural gas (LNG) is shipped to more distant markets.
According to the IEA, natural gas plays a substantial part in the process of satisfying
the world's need for energy.
1.4.2 Energy Trade in Crisis Periods
Regular patterns might be disrupted during crisis times like geopolitical wars, natural
disasters, or global economic recessions, necessitating techniques and solutions. A
crisis may bring about sudden changes in supply chains. Geopolitical tensions that led
to the 1973 oil embargo are an example of how political choices may significantly
influence the supply environment. The recent Russia-Ukrainian conflict has gone
beyond the battlefield, resulting in repercussions for the energy industry. One of the
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biggest changes in the global energy market in decades as a result of the disruption of
the flow of crude oil, natural gas, and refined goods like diesel, caused a significant
and permanent shift in the world's oil market, leading to new geopolitical alliances
comparable to the Arab Oil Embargo of the 1970s (Northam, 2023). For natural Gases,
a disruption in the supply chain causes volatility. There is a possibility that prices could
skyrocket, and there may also be shortages, which will undermine energy security. For
instance, the conflict between Russia and Ukraine in 2014 resulted in disruptions in
the supply of natural gas to Europe (Stulberg, 2017). These disruptions brought to light
the dangers of over-reliance on a single supplier. As a result, governments are looking
more seriously into diversifying their sources and channels, as well as investing in
their capacity to store supplies, to protect themselves against any future crises.
Global occurrences like the COVID-19 Pandemic caused a global economic hit,
leading to abrupt decreases in demand because they imposed constraints on commerce
and travel (Norouzi, 2021). On the other hand, unanticipated demand pressures might
result from unexpected economic booms. Also, Price volatility frequently follows
catastrophes. Sharp price variations can occur when supply shocks and demand shifts
combine. This may be observed in the oil price war of 2020, where both a supply
surplus and a decline in demand resulted in historically low prices. However,
governments frequently keep strategic oil reserves to ensure market stability during
supply shortages (OPEC, 2019). To manage the local economic impact in times of
crisis, policy measures like price restrictions, subsidies, or the deliberate release of
reserves may be used. Crude oil, being such an important commodity, a cooperation
agreement between OPEC and other significant producers throughout successive oil
crises suggests that international coordination may be required to stabilise the global
crises when the need arises (OPEC, 2019). The lessons learned during the COVID-19
Pandemic of 2019 and the Russia/Ukraine crisis of 2022 denote that international crude
oil trading will continue to affect policies and tactics for the future as the globe faces
enormous shifts in energy use, climate concerns, and geopolitical realities (Norouzi,
2021). The worldwide crude oil and natural gas trade relies on existing agreements,
transparent market procedures, and infrastructure investments during normal times.
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Contrarily, times of crisis frequently call for quick reactions, strategic reserves,
governmental intervention, and international cooperation. Various Oil crises and
events have affected the trade of crude oil and by extension the economic conditions
and fortunes of trading nations.
Table 1: Oil and Gas Trade Crises
YEAR
EVENT
1970
Oil Crises of the 1970s
1990
Iraq/ Kuwait Invasion
2007-2008
Market Speculation
2019-2020
Covid 19
2021
Russia/Ukraine war
Source: Montgomery (2022)
1.5 Developed, Developing, and Least Developed Nations Classifications
Nations across the globe have been classified according to their degree of
development. The classification helps with country comparison and contrast based on
predetermined criteria, which promotes international collaboration, trade agreements,
the distribution of aid, and policy formation (World Bank, 2020). Nations are divided
into 3 categories: Developed, Developing, and Least Developed nations. They are
categorised by evaluating the economic, social, and living standards or conditions of
the nation and its populace. Various variables used in this classification include GDP
per capita, Industrialization level, health care, and educational standards. The World
Bank uses Gross National Income (GNI) per capita to classify countries according to
predetermined income levels (World Bank, 2020). The United Nations Development
Programme uses the Human Development Index (HDI), which takes into account
elements including life expectancy, income, and education to give a more
comprehensive picture of progress (UNDP, 2020). Several other international
organisations and think tanks also categorise countries based on standards like political
stability, technical development, or gender equality. These categories, which are
developed via thorough study, data analysis, and examination of various economic and
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social factors, are frequently revised to reflect changes in economic environments.
Beyond simple classification, understanding the intricacy and distinctive features of
each country's categories' growth track is vital (Nielsen, 2012).
1.5.1 Developed Nations
Developed nations are High-Income Countries that have developed booming industrial
and service sectors, high GDP per capita, and advanced healthcare and education
systems (Syed et al., 2012). They usually have highly diverse economies, trade
agreements, and partnerships that play a vital role in international trade. Most
Developed Nations Manufacture goods that use crude oil as fuel. These include
airplanes, cars, home heating machines, and heavy machinery (Britannica, 2021).
Developed nations are also concerned about how using crude oil would affect the
environment and contribute to climate change. These issues are increasingly
influencing global trade and related policies. Switching from fossil fuel to renewable
energy sources has become a priority for many developed nations, thus altering their
trading patterns (EIA, 2016).
1.5.2 Developing Nations
Developing Nations are also known as Upper-Middle Income Countries or Emerging
economies. These nations are distinguished by quick industrialization, expansion in
the service industry, as well as improving living standards (World Bank, 2020). In
developing countries, crude oil is termed ‘black gold’ as it plays a crucial role in their
economies (Norouzi & Fani, 2020). Developing nations generate income mainly from
exports (Henn et al., 2013). Overestimating the impact of crude oil on the geopolitical
positioning, economic viability, and international trading patterns of the developing
nations can be difficult. The World Bank (2020) states that many oil-rich developing
countries heavily rely on crude oil exports as their main source of income. For instance,
Angola, Venezuela, and Nigeria are a few nations that constantly show this tendency.
There are dangers associated with over-dependence on a single commodity or service.
When a country's whole economic foundation depends on oil, it is vulnerable to the
vagaries of fluctuations in the world oil market (Taghizadeh Hesary & Yoshino, 2015).
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Crude oil improves a nation's geopolitical position on the world stage and entices
foreign investment. However, it can also cast a shadow over other key industries,
maintaining an uneven path for economic growth (Lipsky, 2009). The economic
characteristics that most commonly sets developing countries apart is their lower GDPs
per capita. There are two clusters of developing countries with a particular category
closer to developed countries and the other closer to least developed countries. The
ranges in GDP between the top developing nations and the lowest of developing nations
can be huge. However, some countries in the developing classifications are considered
economically stable.
1.5.3 Least Developed Nations
Low-income economies struggle with issues including pervasive poverty, slow
industrialization, healthcare, and education. Thus, LDCs, a phrase the United Nations
used to identify the countries with the weakest economies, fall into one of these
categories (UNCDP, 2020). Three factors: income, human resources, and economic
vulnerability are used by the UNDP to determine least developed countries (LDCs).
46 nations are currently considered LDCs and these nations experience fundamental
difficulties that obstruct their sustained development. Notably, they frequently have
constrained resources, and undiversified economies, and deal with a wide range of
societal issues including high rates of poverty and low educational levels (UNCDP,
2020). International trade has traditionally been considered a possible tool to help these
nations out of their economic difficulties. Global trade trends, however, are not always
in their favour. The world's least developed nations struggle to enter global markets as
a result of their inability to compete favourably (WTO, 2022). As a result, trading with
these nations is severely constrained. By seizing the chances provided by global trade,
these countries may be able to increase their income and promote economic growth.
The LDCs face significant obstacles when striving to gain access to international
markets due to infrastructural deficit, limited finance, and low levels of education and
expertise, hence only contributing about 1.1% of global commerce in 2020 (WTO,
2021). A small number of primary commodities are frequently exported by LDCs,
which makes them particularly sensitive to fluctuating global market prices
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(UNCTAD, 2019). Their inability to produce goods with value-added, which limits
their ability to generate money through exports thus limiting their economic growth.
1.6 Problem Statement
The disparities in development levels among developed, developing, and least
developed nations are not diminishing as anticipated, despite worldwide endeavours
to mitigate and maybe eliminate them. Many internationally coordinated initiatives
appear to be overly broad in their approach, without the specificity required to
effectively address the unique characteristics and circumstances of each nation.
General interventions include initiatives such as the MDGs, which have since evolved
into the SDGs.
Developing and least developed nations often exhibit a proclivity to emulate and adopt
the economic strategies or models employed by developed nations, in the pursuit of
attaining accelerated economic progress. Due to varying circumstances, the majority
of these adopted strategies are unsuccessful in attaining the intended outcomes. Hence,
it is crucial to undertake an examination of energy trade patterns of the various country
categories of the United Nations focusing on significant and impactful strategies with
the view to adapting them to the peculiarities of other nations for economic
development. Economic development has been variously linked to energy
consumption. Thus, this study evaluates the economic implications of international
energy trade across Developed, Developing, and Least Developed Nations. It
therefore focuses on examining the trade patterns and the link between crude oil and
natural gas trade and gross domestic product (GDPs). It further tests the causal
relationship between energy use and economic growth.
1.7 The Research Aim
This research aims to evaluate the economic implications of international energy trade
(vis-à-vis crude oil and natural gas) on the economies of developed, developing, and
least developed countries.
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1.8 Research Objectives
a. To determine the implications of international energy trade on the economies
of developed, developing and least developed nations.
b. To determine the implications of energy consumption on the economies of
developed, developing and least developed nations.
1.9 The Research Questions
i. How does international energy trade impact the economic development of
nations vis-à-vis developed, developing and least developed nations? ii. How
does per capita energy consumption impact the economic development of nations
vis-à-vis developed, developing and least developed nations?
1.10 The Scope of the Study
The study covers the developed, developing and the least developed nations in a broad
sense and not country-wise analysis. The data for this study covers a period from 1995
to 2021 and were obtained from secondary sources. Economic development of nations
was viewed from a per capita GDP perspective. International trade in crude oil
variables was also limited to values per capita in millions of USD.
1.11 Significance of the Study
In accordance with the stated aim and objectives of this research, it is anticipated that
the findings will hold substantial implications for nations, particularly those classified
as developing or least developed. These nations will be able to assess the intricacies of
international trade in crude oil and natural gas, as well as the trading patterns of
developed countries, in order to implement crucial strategies aimed at achieving
economic benefits. Therefore, the results of this study will provide valuable insights
for stakeholders and policy makers to optimally allocate resources, focusing on trade
patterns that foster economic growth.
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This study will also have relevance for all countries engaged in oil and gas trading,
international trade organisations, as well as research material in the area of economics,
statistics, international trade and development.
1.12 Structure of the Study
This research has been structured into six chapters in order to provide a logical and
coherent flow of ideas, hence facilitating understanding. Chapter one provides a
comprehensive introduction to the subject matter, ultimately leading to the formulation
of the problem statement and the establishment of research objectives. Chapter two of
this research paper encompasses a comprehensive literature analysis that delves into
relevant studies, methodologies employed, and consequent discoveries. Accordingly,
this review establishes the research gap that this study aims to address. Chapter three
of the study focuses on the aspects of data and methodology, which include the
identification of variables, the gathering and presentation of data, and the use of the
chosen technique for data analysis. Chapter four provides a comprehensive exposition
of the findings derived from the data analysis, accompanied by a concise statistical
interpretation of the results. Chapter five provides an in-depth analysis of the research
findings on the impacts of crude oil and gas trade variables on the gross domestic
products (GDPs) of developed, developing, and least developed countries. This
chapter also examines the crude oil and natural gas trade patterns in these countries
and explores the implications of the patterns for global maritime transportation of
crude oil and natural gas.
Chapter six provides a comprehensive overview of the research conducted, focusing
on the outcomes of the analysis and their significance for the three distinct nation
groups. Additionally, the chapter offers suggestions that are grounded in the study's
findings.
1.13 Limitations of the Study
The study was carried out with secondarily sourced data that covers between year 1995
and 2021. The timeframe places some limitation to the applicability of the findings in
explaining events before or after this time. There were cases of incomplete observation
19
especially from the least developed countries. However, this was addressed by the
panel regression which makes up for such missing values.
Chapter 2 - Literature Review
2.1. The Role Of Energy In Economic Development
The role of energy in the economic development of nations has been of significant
importance throughout history, as it serves as an essential and predominantly
indispensable factor in the production process. It is worth noting that oil and gas, which
account for approximately two-thirds of global energy consumption, have been the
primary sources to meet the world's energy demands (Bashiri Behmiri & Pires Manso,
2013).
According to the Corporate Finance Institute, (2023), over a third of the world's energy
consumption has historically come from crude oil, while OPEC, (2010) put the figure
at 40% of the global energy mix, making crude oil one of the most important fuel
sources. Due to the significance of crude oil as an energy source, it has an extensive
market that includes both physical and derivatives trading (Corporate Finance
Institute, 2023). The Organization of Petroleum Exporting Countries (OPEC) claimed
that throughout the 20th century and into the 21st century, crude oil's pre-eminence has
paralleled the immense economic advancements made as four-fifths of this
development is estimated to have occurred in the second half of the 20th century,
beginning with the period of reconstruction, leading to a significant increase in energy
consumption, following the second world war (OPEC, 2010)
After World War II, according to OPEC, oil became the dominant energy source
worldwide, with the OECD consuming between 60 and 70 percent of all oil produced.
During this time period, both total and per capita energy use were significantly lower
in developing countries but this trend is starting to change as consumptions of gas have
increased consistently in both OECD and developing countries (OPEC, 2010).
20
In recent years, however, there has been an observable inclination among nations to
reduce their energy consumption. This trend can be attributed primarily to the
deterioration of the environment and climate change concerns caused by oil
exploration as well as the significant increases in crude oil prices. Consequently, there
has been a heightened emphasis on examining the relationship between energy usage
and the economic growth of nations (Behmiri & Pires Manso, 2014).
2.2. Previous Research Findings
Several prior studies have looked at how energy use affects GDP growth over time,
however, further investigation is needed to enhance our understanding in this area from
a different perspective.
Research was conducted on the correlation between increasing economic activity and
its impact on energy consumption, as well as the reciprocal relationships. Several of
these studies demonstrated positive relationships between economic growth and
increased energy consumption (Sama & Tah, 2016), but not only crude oil and
gasgenerated energy.
Different academic views exist on the causality between energy use and economic
development, as shown by the results of econometric analysis. These differences could
be attributed to factors such as econometric approaches or analytical tools, historical
periods covered, countries' varying climates and geopolitical differences, economic
growth plans, as well as energy output and consumption rates (Sama & Tah, 2016).
Crude oil and petroleum products are vital for energy generation for economic
activities and house use and are frequently traded globally (Zhang et al., 2018).
However, there is no consensus on the impact of energy consumption and/or trade on
economic growth.
In their study, Bildirici and Bakirtas (2014) employed an ARDL (Autoregressive
Distributed Lag Bounds) testing methodology to examine the influence of
international trade in crude oil on the economic development of a selected group of
countries. The study utilised data from Brazil, Russia, India, China, Turkey, and South
Africa spanning the years 1980 to 2011 and the findings of the study indicate the
21
presence of a significant bidirectional causal relationship between oil energy
consumption and GDP in all of the countries under investigation, suggesting a
longterm impact.
Žiković and Vlahinic-Dizdarević (2011) examined the potential existence of a causal
association between oil consumption and economic growth within the context of small
European countries. The time frames considered for this analysis were 1980-2007 for
small developed European economies and 1993-2007 for transition economies. It was
found that in the case of the most developed European countries and certain transition
economies, there exists a causal relationship wherein real GDP influences oil
consumption. Conversely, the less developed European countries exhibited a
directional relationship where oil consumption influenced economic growth. The
result showed a distinction between the impact of crude oil consumption in developed
European countries and less developed small European countries. That is to say that
economic development drives the demand for crude oil consumption in most
developed European countries whereas the consumption of oil drives economic
development in less developed European countries.
Žiković and Vlahinic-Dizdarević (2011) also demonstrated that the causality in the
developed European nations was influenced by the presence of a well-advanced
postindustrial society characterised by a robust tertiary sector. Conversely, in the
economies undergoing transition, the causality can be attributed to the phenomenon of
deindustrialization and the subsequent transition depression. These factors resulted in
a significant decline in the industrial sector and a consequent decrease in the demand
for crude oil (Zikovi & Vlahinic-Dizdarevic, 2011). Moreover, the research findings
signposted that greater levels of crude oil consumption were indicative of heightened
levels of industrialization and economic advancement among the less developed
European nations. Consequently, it was suggested that increased financial resources
should be allocated towards subsidising oil prices and ensuring the acquisition of
stable, sustainable oil supplies. This recommendation was based on the positive
influence that such measures would have on the economic growth of the least
developed European countries (Zikovi & Vlahinic-Dizdarevic, 2011).
22
In their study, Bashiri Behmiri and Pires Manso (2013) employed a multivariate panel
Granger causality framework to investigate the causal association between crude oil
consumption and economic growth in a sample of 23 Sub-Saharan African countries
during the period spanning from 1985 to 2011. The researchers utilised crude oil price
as the control variable in their model and discovered that, in the short term, there exists
a bidirectional causal relationship between crude oil consumption and economic
growth in economies that import oil. Additionally, a positive correlation was observed
between these two variables in economies that export oil. However, it was noted that
there exists a significant and reciprocal causal relationship between the Gross
Domestic Product (GDP) and the consumption of crude oil in both regions. Therefore,
Bashiri Behmiri and Pires Manso (2013) concluded that a reduction in crude oil
consumption, in the absence of appropriate regulations, exerts a detrimental impact on
the economic growth of Sub-Saharan Africa.
Behmiri and Pires Manso, (2014) also investigated the relationship between the
economic development of Latin America and crude oil consumption. Using the
framework of panel regression, they examined the relationship between several
regions, including six Caribbean, six Central American, and eight South American
nations. The findings of the study indicated that there is no Granger causality between
economic growth and crude oil consumption in the examined regions. This implies
that policymakers can implement crude oil conservation policies without incurring
substantial negative economic consequences. The study additionally revealed that
there exists a positive, long-term relationship between crude oil consumption and GDP
in Central America. Specifically, a 1% increase in crude oil consumption leads to a
0.16% increase in GDP, indicating the relatively low responsiveness of GDP to
fluctuations in crude oil consumption. Based on this discovery, it was advised that the
implementation of crude oil conservation strategies in such regions should be
approached with increased caution.
Sama & Tah, (2016) established that GDP, population growth, and the prices of
petroleum are positively related to energy use. After researching the impact of energy
consumption on economic growth in Cameroon from 1980 to 2014 using the
23
Generalised Method of Moments. The study further revealed that since economic
growth is directly correlated with energy production and consumption, expanding
alternative energy sources like solar, wind, and thermal energies will be beneficial for
economic development. In other words, barring the availability and sustainability
advantages of green energy sources, increasing crude oil consumption in Cameroon
will further improve the country’s economic development.
Bhusal (2012) looked into what role crude oil plays in the economy of Nepal and how
that can affect GDP. Short-term and long-term effects were examined using yearly
data from 1975 to 2009. Employing the Granger causality test, evidence of short and
long-term reciprocal Granger causality between oil consumption and economic growth
was observed. These two variables share the same order of cointegration (I (1)),
suggesting that they are highly correlated.
Sultan & Alkhateeb, (2019) noted that the 1970s oil price shock had a profound effect
on economies all around the world. It found that energy consumption and actual output
were found to interact, but the direction of causality between the two could not be
established. Moreover, the study revealed a sustained equilibrium between energy
consumption and actual economic production in India over an extended period, as
evidenced by the analysis of data spanning from 1971 to 2014. According to Sultan
and Alkhateeb (2019), the findings of the study indicate the presence of a
unidirectional association between energy and India's economic development in the
short term, while a bidirectional relationship is observed in the long term.
An alternative approach to assessing the economic implications of crude oil involves
examining the effects of price fluctuations on two distinct categories: countries that
are net importers of crude oil and countries that are net exporters of crude oil. Behmiri
and Pires Manso (2014) assert that a positive shock in crude oil prices leads to an
increase in the purchase price of crude oil for net importing countries. This, in turn,
may have detrimental effects on their economic growth. Conversely, net exporting
countries experience a positive impact on their economic growth as they can sell oil at
higher prices. It is important, however, to note that while this may be advantageous in
the short term, in the long-term these countries may face negative consequences due
24
to the global crisis that occasioned the rise in oil prices. Accordingly, the effect of an
oil price surge or crude oil consumption on a nation's economic activity depends on
whether the nation is a net oil importer or exporter (Behmiri & Pires Manso, 2014).
2.3 The Energy Market Dynamics
Energy plays a central role in the course of development by facilitating investments,
fostering innovations, and nurturing emerging industries, thereby serving as the
driving force behind job creation, inclusive economic growth, and the promotion of
shared prosperity at a macroeconomic level (World Bank, 2023). However, about 675
million people continue to lack access to electricity (World Bank, 2023).
Approximately 2.3 billion individuals engage in the utilisation of fossil fuels for
cooking or heating their residences, thereby posing detrimental effects on both their
well-being and the surrounding ecosystem, according to the World Bank 2023 report.
Despite this global challenge, occasional shocks in the energy market further
compound the existing energy crisis. The World Bank (2023) reported that from the
onset of 2022, the global energy markets experienced a substantial disruption of
unprecedented magnitude. This disruption was attributed to the effects of the
COVID19 pandemic, along with the current conflict in Russia and Ukraine, which has
contributed to increased volatility in energy prices resulting in worsening energy
shortages and raising concerns about energy security. Furthermore, these factors have
impeded advancement in achieving universal access to affordable, reliable,
sustainable, and modern energy by the year 2030, as outlined in SDG 7 of the United
Nations.
Energy price shocks have a significant impact on a majority of countries, with
developing and least developed nations bearing the greatest burdens, particularly those
that rely on energy imports. The insufficient capacity to address energy price
fluctuations has resulted in energy apportioning in certain nations and an increase in
poverty levels.
Like in a typical competitive market, the forces of demand and supply largely
determine the world energy outlook and key factors to consider in this regard are the
drivers of energy demand (Watchwire, 2018). Similar to other commodity markets, the
pricing of electricity is determined by these forces. When the quantity demanded
25
exceeds the quantity supplied, prices tend to increase, and conversely, when the
quantity supplied exceeds the quantity demanded, prices tend to decrease. During
periods of extreme cold in winter, there is a notable increase in prices due to the
competition between power generation and heating systems for the limited supply of
natural gas (Watchwire, 2018).
Three key sectors that drive the energy demand are electricity for industrialization and
households, transportation, and heating. In effect, the level of industrialization of a
country may influence its demand for electrical energy. The same goes for
transportation. A highly industrialised nation will need for more energy to improve
and sustain its industrialization and transportation network that keeps its economy
thriving. On the other hand, heating-induced demand for energy follows the climatic
conditions of countries. For instance, the Nordic region of Europe usually experiences
very cold weather conditions for the most of the year and this positively influences
their need for energy for heating. Countries located near the equator experience very
hot weather conditions and will require energy for cooling, hence influencing the
global energy demand. However, during periods of low demand, such as the shoulder
months characterised by minimal requirements for heating or cooling, prices typically
exhibit a stable trend (Watchwire, 2018).
The gradual decline and decommissioning of nuclear, coal, and oil-fired power plants
have resulted in a growing dependence on natural gas-fired generators. The United
States in 2017 generated approximately 32% of electricity using natural gas (EIA,
2022)
2.4 Energy Consumption and Economic Development
Energy demand and consumption drive the trade in crude oil and natural gas. However,
there are varying opinions about energy consumption and per capita GDP. The
discourse around the correlation between energy consumption and per capita GDP has
been a subject of continuing analysis and discussion among academic circles,
governmental bodies, and research communities. There is a contention among scholars
that energy, in conjunction with other variables of production such as capital and
26
labour, plays a significant role in driving economic growth (Huseyin Kalyoncu et al.,
2013). Conversely, there exists a viewpoint positing that energy consumption is just a
small fraction of the gross domestic product (GDP) and lacks much influence on the
trajectory of economic development.
It is crucial to admit that our examination of international trade of energy primarily
focuses on the monetary values of these trades, rather than the energy consumption
within a country. It is recognized that an increase in trade values of crude oil and
natural gas by a nation during a certain time frame might potentially indicate a rise in
demand, probably due to increasing consumption. However, it is important to note that
this correlation may not always hold.
The existing body of research presents varying perspectives on the correlation between
energy usage and economic development. The diverse empirical findings may be
explained by differences in the time frame considered, the variables are chosen, the
geographical area of emphasis, and the econometric methods utilised (Huseyin
Kalyoncu et al., 2013), as demonstrated in several research mentioned hereunder. In
their study, Yu and Jin (1992) employed the Bivariate Granger Test to demonstrate the
absence of a causal association between energy consumption and economic growth in
the United States, a nation classified as developed. Similarly, Stern (1993) employed
the Granger Causality Test to establish the lack of a causal relationship between
economic progress and energy consumption in the United States.
Masih and Masih (1996) employed the Sims Causality and Granger Causality
frameworks to examine the association between economic growth and energy
consumption in several countries, namely Malaysia, Singapore, Philippines, India,
Indonesia, and Pakistan. The findings of their analysis revealed that no significant
relationship exists between economic growth and energy consumption in Malaysia,
Singapore, and the Philippines. However, in the case of India and Indonesia, energy
consumption was found to have a unidirectional impact on economic growth.
Conversely, in Pakistan, the relationship between energy consumption and economic
growth was found to be bidirectional.
27
Yu and Choi (1985) utilised the Granger Test to examine the causal relationship
between energy consumption and economic growth in several countries, including the
United States, the United Kingdom, Poland, South Korea, and the Philippines. Their
findings indicated that no causal influence was seen between energy consumption and
economic development in the US, UK, and Poland. However, they did find evidence
suggesting that energy consumption leads to economic development in South Korea
and the Philippines.
Moreover, Glasure and Lee (1998) employed the Bivariate Vector Error Correction
Model (VECM) to demonstrate the presence of bidirectional causation between
economic growth and GDP in South Korea and Singapore. Similarly, Cheng (1999)
demonstrated that in the context of India, there exists a positive relationship between
economic growth and energy use.
Asafu-Adjaye (2000) used the Trivariate Vector Error Correction Model (VECM), to
show that energy consumption in India and Indonesia has unidirectional positively
associated with economic growth. However, in the case of Thailand and the
Philippines, a bidirectional causal relationship was seen between economic growth and
energy consumption.
Soytas and Sari (2003) employed a Bivariate Vector Error Correction Model (VECM)
to demonstrate the causal effects from economic growth on energy usage in Turkey
and South Korea. Conversely, their findings indicate that in Argentina, Canada, the
USA, and the United Kingdom, there exists a mutual impact between energy use and
economic growth.
In their study, Fatai et al. (2002) employed the Granger causality test to determine
whether there was a statistically significant association between economic
development and energy consumption in New Zealand. Their findings led them to
conclude that no such link was seen. Altinay and Karagal (2005) conducted a study
whereby they employed Hsiao's version of Granger Causality to demonstrate the
absence of a correlation between energy consumption and economic development in
Turkey.
28
Narayan and Smyth (2008) employed a multivariate panel Vector Error Correction
Model (VECM) to analyse the relationship between energy consumption and
economic growth in the G-7 nations. Their findings indicated that energy use had a
positive impact on economic development within the G-7 countries. In a similar study
conducted by Ozturk et al. (2010), panel causality was employed to examine the
relationship between economic growth and energy use across 51 countries categorised
as low-income, lower-middle-income, and upper-middle-income. The findings
revealed that in low-income countries, economic growth positively influences energy
use. In middle-income countries, a two-way causality was observed between economic
growth and energy use. However, no significant relationship between energy use and
economic development was found in upper-middle-income countries.
Furthermore, Apergis and Payne (2009) employed a multivariate panel Vector Error
Correction Model (VECM) to examine the causative relationships in 11 nations
belonging to the Commonwealth of Nations. Their findings indicated the presence of
a bidirectional causation between energy consumption and economic development
within these countries.
Moreover, a scholarly investigation conducted by Lee and Lee (2010) employed a
multivariate panel Vector Error Correction Model (VECM) to demonstrate the
existence of bidirectional causation between economic development and energy
consumption across 25 member nations of the Organization for Economic Cooperation
and Development (OECD). In a similar vein, Bekle et al. (2010) employed the Granger
Causation Test to demonstrate the presence of bidirectional causation between
economic development and energy consumption across a sample of 25 OECD nations.
2.4. The Established Gap from Previous Studies
In the above-referenced literature, we see conflicting results which could be attributed
to the time frame covered by the research or the level of industrialization of the country
of study. It is evident also that the studies focused mostly on individual countries or
regional countries. However, there is yet any research that considers the energy
consumption across the World Bank country groupings vis-à-vis developed,
developing, and least developed countries.
29
In most of the existing work, there was broad consideration of energy consumption to
include solar, coal, and other sources of electricity apart from hydrocarbons.
In a study conducted by Samawi et al. (2017), path analysis and structural equation
modeling were employed to examine the relationships between energy supply and
economic growth in oil-importing countries. The researchers investigated both the
direct and indirect effects of energy supply, identifying the linkages and mediating
variables involved in this relationship. The researchers discovered a robust correlation
between energy supply and economic growth, wherein the impact on the economy is
contingent upon the specific energy source and the mediating variables involved.
Although the research focused on the impact of energy, it paid attention to the
oilimporting countries and not the exporting countries. Also, oil-importing countries
cut across the various categories of economies, hence, the study did not show how
patterns of trade in crude oil influence economic development across the three major
economy groupings of the World Bank, which is one of the main thrusts of this
research.
In their study, Sultan and Haque (2018) utilised the cointegration method developed
by Johansen to analyze empirical data from Saudi Arabia. Their findings revealed the
existence of a long-term association between economic growth and variables such as
crude exports, imports, and government consumption expenditure. While Saudi Arabia
is recognized as a developing nation and maintains a significant role as a net exporter
of crude oil, it would be misleading to assume that the effects of crude oil exports in
other developing countries that also engage in net oil exports would be identical.
In a similar research by Gbadebo, (2008) on the impact of the crude oil sector on
Nigeria's economic performance, it was found using Ordinary Least Squares
regression analysis that rising crude oil consumption and exports have boosted the
Nigerian economy. Again, the study focused on a single country’s (Nigeria’s crude)
exports but not imports. Although Nigeria is a net exporter of crude oil, it also imports
large quantities of refined products using various trade models, including crude oil
30
swaps (Gbadebo, 2008). Thus, isolated analysis of countries’ crude oil trade is unlikely
to give a more generally acceptable relationship due to the impact of some intervening
variables from country to country.
In their study, Mlaabdal et al. (2020) proposed a comprehensive approach to analyzing
the cointegration and causal relationships that underlie national economic
development. They employed a two-step methodology, beginning with the application
of a heterogeneous modified ordinary least squares (HMOLS) model to identify a
linear relationship between economic development indicators (such as GDP, capital,
and labour costs) and indicators of national economic functioning (including volumes
of oil production and rent payments for oil). Subsequently, they employed the Granger
method based on a developed time series model known as the Vector Error Correction
Model (VECM) to determine the causal links between national economic growth, oil
production, and rent payments. This method involved adjusting parameter dynamics
based on the long-term relationships between variables and their deviations. The
findings of Mlaabdal et al. (2020) indicate that there exists cointegration and causal
relationships between the development of the oil sector and the overall national
economy. Specifically, the analysis reveals that both oil output and rent payments have
a positive impact on the gross domestic product (GDP) of countries belonging to the
Organisation of the Petroleum Exporting Countries (OPEC), as well as high-income
and middle-income nations. However, it is noteworthy that in low-income countries, a
10% increase in oil production leads to a relatively smaller increase of 0.2% in GDP.
While the research conducted by Mlaabdal et al. (2020) primarily concentrated on the
crude oil production in high, middle, and low-income countries that are net exporters
of crude oil, it did not investigate the influence of crude oil on the economies of high,
middle, and low-income countries that are net importers of crude oil. This research
aims to fill this knowledge gap as well.
Accordingly, considering the relevance of crude oil and natural gas in energy
generation across economies (and its impact in the foreseeable future), it is considered
pertinent to study how trade in crude oil and natural gas, as well as their consumption
31
impact the three broad economic classification as developed, developing and least
developed nations, using GDP as an approximation for economic development.
2.5 The Research Focus
Given the foregoing, this research work is aimed at investigating if there is a significant
relationship between international energy trade (crude oil and natural gas) and GDP
within the framework of developed, developing, and least developed countries. We
seek to establish a pattern of development across the three major categories of
economies based on their trade in crude oil and natural gas, as well as total energy
consumption. In other words, using crude oil, natural gas, and other petroleum
products’ import and export data as the independent variables, this study aims to
determine if, and how the GDPs of the three categories of economies respond to
changes in these independent variables over time.
Therefore, it is imperative to conduct an investigation and ascertain a discernible
pattern of crude oil and natural gas trade across different country groupings. This will
facilitate the establishment of a more universally recognized correlation between
international trade in crude oil and natural gas, and the economic development of these
respective country groupings.
In the absence of additional factors that impact the economic development of nations,
the establishment of a crude oil trade pattern in developed countries may serve as a
valuable reference for developing and least developed economies. Such a pattern can
offer insights on actions to undertake, actions to avoid, or actions to terminate to
promote the economic development of these countries.
To achieve this, the analysis is carried out in three broad categories of economies as
provided by the World Bank (2020) as follows:
⮚ Developed economies/countries
⮚ Developing economies/countries
⮚ Least developed economies/countries.
This grouping is to examine the relationship or impact that these trade patterns have on
the GDPs of countries within the different economic categorization.
32
The findings of this study will be beneficial to all economies in terms of crude oil and
natural gas trade, and energy consumption policies.
Chapter 3 - Research Method And Data
3.1 Research Method
All research projects need a technique to help the researcher define the problem, collect
data, and draw conclusions about the relationship between the independent and
dependent variables (Bazeley, 2013). To understand or establish the natural
relationship between GDP and international trade of energy, a quantitative model is
imperative. Accordingly, a panel regression technique has been identified to suit the
objectives, data, and the hypothesis of this research work.
3.2 Identification And Justification Of Variables
Several variables influence the GDP of a nation. Some are quantitative in nature and
therefore are measurable while others are qualitative and cannot be measured. Since
this study focuses on the economic implications of international energy (crude oil and
natural gas) trade and the economic development of nations, using GDP per capita as
an approximation for economic development, related variables have been identified.
Accordingly, crude oil production, crude oil export/import, other petroleum products
export/import (excluding crude oil), natural gas import/export, energy consumption,
oil electricity, and gas electricity were identified as independent variables with GDP
per capita as the dependent variable.
3.2.1 Gross Domestic Product per Capita (Dependent Variable - Y)
To examine the influence of energy trade on the economies of countries as classified
by the United Nations, GDP is considered a suitable indicator for assessing the
economic development of a nation. GDP is the conventional metric used to quantify
the value generated by the production of goods and services within a specific country
over a given timeframe (OECD, 2023). It quantifies the revenue generated from said
production or the aggregate expenditure on end products and services (excluding
imports).
33
According to Callen (2022), the concept of GDP involves the quantification of the
monetary worth of final products and services, namely those acquired by consumers,
that are generated inside a country's borders during a designated period, such as a
quarter or a year. As a result, GDP serves as a comprehensive measure of all the
economic production created within a nation's territorial confines. GDP includes both
marketable goods and services, as well as non-market activities such as
governmentprovided defense or educational services (Callen (2022). The significance
of GDP lies in its ability to offer insights into the magnitude and well-being of an
economy, given that real GDP growth is often employed as an indicator of the
economy's general state. There are three distinct perspectives through which GDP can
be analysed. Firstly, the value-added at each stage of the production approach entails
computing the total sales figure while subtracting the cost of intermediate
manufacturing inputs. Secondly, the expenditure method involves determining the
value of final consumers' purchases. Lastly, the income strategy involves aggregating
the revenues generated from production (Callen, 2022).
However, GDP alone may not adequately reflect the material well-being of individuals
within a country (OECD, 2022). Therefore, alternative indicators may be suitable for
capturing this aspect of people's welfare in respect of a country’s overall economic
well-being. Generally, an increase in real GDP reflects a positive correlation with a
nation's economic well-being. As an approximation for economic development, this
study uses GDP as the dependent variable and would be sourced for each of the
countries under their categories (developed, developing, and least developed) for the
period covering 1995 and 2021.
3.2.2 Crude Oil Production per Capita (Independent Variable X1)
The quantity of oil recovered from the earth after the removal of inert materials and
contaminants is referred to as crude oil production. It consists of crude oil, Natural Gas
Liquids (NGLs), and other additives (OECD, 2019). Crude oil production is a critical
factor in the crude oil trade. Thus, for a meaningful study on the impact of crude oil
trade on the economies of trading nations, there is a need to understand crude oil
production about crude oil trade. In essence, it is general economic knowledge that the
production and supply of crude oil is critical in meeting global energy demand. Thus,
34
volatilities in the demand and supply dynamics affect international trade in crude oil
and the supply of crude oil is a function of its production.
Crude oil is also referred to as the lifeblood of the contemporary international energy
infrastructure. It is not just the primary energy source, but also the primary source of
income which helped the development and wealth of the Western world. Due to
constraints caused by peak oil, the future supply of oil is uncertain and may potentially
decline despite being essential to every facet of modern life (Mikael, 2009). The main
suppliers of crude oil in the global market are the OPEC and non-OPEC countries. The
behaviour of these two groups in crude oil production determines the supply and price
of crude oil in the global market barring the influence of other factors.
OPEC is an intergovernmental organisation that was established during the Baghdad
Conference held from September 10-14, 1960 with Iran, Iraq, Kuwait, Saudi Arabia,
and Venezuela as founding members (OPEC, 2022). Over time, the organisation has
expanded to include 13 member nations. The primary goal of OPEC is to facilitate the
coordination and harmonisation of petroleum policies among its member nations. This
objective aims to ensure equitable and stable pricing for petroleum producers, as well
as guarantee a consistent cost-effective, and reliable supply of petroleum to all nations
that consume it. Additionally, OPEC seeks to provide a justifiable return on investment
for individuals and entities that have invested resources in the petroleum industry
(OPEC, 2019). OPEC has consistently maintained a significant presence in the global
oil market by effectively managing crude oil production levels among its member
nations through the implementation of quotas. As a result, OPEC exercises
considerable influence over global crude oil supply, pricing dynamics, and trade.
Kisswani et al. (2022) analyzed the influence of non-OPEC oil supply on the
production level of OPEC oil production. This examination was carried out by
employing the Quantile Autoregressive Distributed Lags (QARDL) model, which
enables the investigation of both short-term influences and long-run cointegrating
35
relationships across various quantiles. The researchers utilised monthly data spanning
from January 1993 to March 2020 for their analysis. The primary results indicate that
the impact of non-OPEC production on OPEC production exhibits symmetry in the
long term, while being contingent on quantiles in the short term (Kisswani et al. 2022).
Also, in the short term, a substantial reduction in OPEC production as a result of an
upsurge in non-OPEC production was noted. Nevertheless, over time, the growth in
non-OPEC production leads to an escalation in OPEC production. Additionally, the
findings indicate that there is a positive relationship between oil prices and OPEC
production in both the short-term and long-term (Kisswani et al. 2022).
Loosely using crude oil import and export data to signify consumption in a nation could
be misleading because international trade guarantees that not all imported commodities
are completely consumed in the importing country. There is a possibility of
transshipment or crude oil refining to generate other products. In some instances,
imported crude oil may be refined and exported to other countries. Thus, reflecting
that not all crude oil imports into an economy translate to energy consumption. Hence
the a need to consider crude oil production as an independent variable in the analysis
of the impact of international trade in crude oil on the economic development of
nations.
3.2.3 Crude Oil Export per Capita (Variable – X2)
Crude oil export was considered in this study as an independent variable since it is seen
to influence the economies (GDP) of trading nations. International trade in crude oil
encompasses crude oil export or import or both.
According to Workman (2023), the global export of crude oil reached a total value of
US$1.35 trillion in 2022, making it the most valuable product exported worldwide.
This surpasses the previous year's leading export, which was electronic integrated
circuits and related parts. The proportion of crude petroleum oils in the aggregate
export of commodities witnessed an increase from 4.6% in 2021 to 5.6% in 2022
(Workman, 2023).
36
The research conducted by Esfahani et al. (2012) established a long-term relationship
between output and oil income in a significant crude oil-exporting economy. This study
expands upon the stochastic growth model developed by Binder by incorporating oil
exports as an additional factor in the process of capital accumulation. Specifically, the
analysis reveals the presence of long-run relationships between real output, foreign
output, and real oil income in six out of the nine economies that were examined
(Esfahani et al. 2012).
The aforementioned studies suggest that the export of crude oil plays a significant role
in a country's economic development. Therefore, it is appropriate to include crude oil
export as an independent variable in this study. The aim is to examine the nature of the
relationship between economic development and crude oil export across three different
categories of nations.
3.2.4 Crude Oil Import per Capita (Variable -X3)
One additional factor that requires attention in the examination of the impact of energy
trade on economic development is the value of crude oil imports by various nations
groups. Generally, the economic contribution of crude oil trade to any nation should
extend beyond the revenue generated from the sale of crude oil in terms of foreign
exchange earnings. The importation of crude oil also plays a significant role in the
economic value chain of a nation by providing energy support, creating employment
opportunities, and adding value through refining processes, among other contributions.
As an illustration, Kim and Baek (2013) noted that crude oil fulfills approximately
45% of Korea's primary energy requirements. The industrial sector in Korea is
responsible for approximately 56% of the overall crude oil consumption. However,
due to the absence of established domestic oil reserves, Korea is entirely dependent on
imports to fulfill its demand for crude oil. Consequently, the economic growth driven
by energy-intensive industries leads to a significant surge in the importation of crude
oil in Korea. The importation of crude oil in Korea has experienced a steady growth
trajectory since 1989, resulting in its ascent to the position of the seventh-largest oil
consumer and fourth-largest oil importer globally in 2009 (Kim & Baek, 2013).
37
One fiscal trend observed in Ghana was the practice of financing a substantial portion
of crude oil importation through export earnings. In 2007 alone, approximately 50.2%
of the country's export earnings were allocated towards financing crude oil purchases,
thus establishing the influence of crude oil imports on Ghana's national economy
(Marbuah, 2018) and supporting the inclusion of crude oil imports as one of the
explanatory variables in our study.
Unfortunately, a significant number of nations across the globe lack substantial
reserves of crude oil. Consequently, to fulfil their energy needs and sustain industrial
output, these countries heavily rely on the importation of crude oil. Energy
consumption plays a central role in economic development and growth (Sadorsky,
2011). Given the significance of crude oil to nations, those with limited or non-existent
crude oil resources within their territories depend on importing crude oil to fulfill their
energy requirements for energy generation. Therefore, crude oil import value is
regarded as a significant factor when examining the effects of international energy
trade from the perspectives of developed, developing, and least developed countries.
3.2.5 Other Petroleum Product Export excluding Crude Oil per capita (Variable -X4)
Crude oil is source material for many other by-products including but not limited to
aviation turbine fuel, petrol, diesel, kerosene, fuel oil, napalm, polyurethane, paraffin,
naphtha, naphthalene, plastic, bitumen, polyester, and liquefied petroleum gas (The
Editors of Encyclopaedia Britannica, 2016). Trade in these petroleum products is
considered to affect the economies of nations. For instance, the use of aviation fuel in
any nation may indicate how developed and viable its aviation industry is. More so,
the by-products traded or exported vary from nation to nation depending on
comparative advantages. Thus, exports of petroleum by-products by nations could
have a significant impact on their economy (per capita GDP), hence the inclusion of
other petroleum products exported (excluding crude oil) as an independent variable for
this study.
To buttress the inclusion of this variable, research conducted by Azretbergenova and
Syzdykova (2020) examined the "Dependence of the Kazakhstan Economy on the Oil
38
Sector and the significance of Export Diversification," revealing the significance of
petroleum products about Kazakhstan's overall economic landscape. Approximately
50% of budget revenues in Kazakhstan are derived from oil and petroleum products
export, depicting a significant reliance on oil-related income which led to the
depreciation of the national currency (KZT) by 20% and 60% respectively, during the
first and second stages of oil prices decline in 2014 (Azretbergenova & Syzdykova,
2020).
Pirlogea and Cicea (2012), studied the relationship between energy consumption by
fuel and economic growth in Spain, Romania, and EU employed a three-step
methodology using data from 1990 – 2010. It established that in the long run, there is
evidence of a correlation between energy consumption from total petroleum products
and economic growth, as measured by GDP per capita in constant prices while in the
short term, only two relationships were highlighted, both of which support the growth
hypothesis. Hence, the other petroleum products export is included as an independent
variable in this study.
3.2.6 Other Petroleum Product Import excluding Crude Oil per capita (Variable X5)
In a similar consideration as above, it is safe to include other petroleum products
imports to the list of independent variables to be used to explain changes in GDP on
account of international trade of energy.
Fluctuations in global petroleum prices affect both importing and exporting nations
economies. According to Coady et al. (2010), additional evidence to support the notion
that in the absence of policy or behavioral changes, the ratio of the value of net oil
imports to GDP can serve as an indicator of the potential impact, in terms of percentage
of GDP, of a twofold increase in the international price of petroleum. The price of
petroleum products affects GDP but this is mostly possible through the instrumentality
of trade (Coady et al., 2010). Hence, the import value of other petroleum products
(excluding crude oil) is considered to influence the GDP.
39
3.2.7 Natural Gas Export (Variable X6) and Natural Gas Import (Variable X7)
The natural gas export variable represents the total annual value of natural gas export
from a given country to the rest of the world while the natural gas import variable
represents the total annual value of natural gas imports from the rest of the world to a
given country. Natural gas is extensively employed as a fossil fuel due to its
environmental attributes, such as low carbon dioxide emissions, high efficiency in
power generation as well as increasing demand from the industrial sector (UNCTAD,
2012). Natural gas reserves are geographically distributed across various regions. It is
commonly regarded as the preferred fuel option, taking into account both
environmental and economic perspectives. It presents prospects for industrial
development and propels the economies of various nations.
Natural gas consumption and economic growth in the Gulf Cooperation Council
(GCC) nations show a positive co-integration (Ozturk and Al-Mulali, 2015), using a
panel dynamic ordinary least square (DOLS) and completely modified ordinary least
square (FMOLS) methodologies. Since natural gas, as a bridge gas, is widely used for
energy generation across the globe, the inclusion of both the export and import
components of natural gas trade in our variable mix is considered appropriate for this
study.
3.2.8 Total Energy Used (Variable X8)
Energy use encompasses not just the utilisation of electricity but also extends to other
spheres such as transportation, heating, and cooking and it is measured in kilowatt hour
(KWH) per person (Our World in Data, 2023). Understanding the causal link between
energy consumption and economic development provides valuable insights in
formulating effective energy conservation policies (Azam et al., 2015). A reduction in
energy consumption might potentially lead to adverse consequences such as reduced
income levels, higher unemployment rates, or a shortfall in the budget, hence, it is
significant (Huseyin Kalyoncu et al., 2013).
Although several scholars have conducted a study of the correlation between energy
consumption and GDP across various nations a definitive consensus is yet to be
achieved (Huseyin Kalyoncu et al., 2013). The divergent empirical findings can be
40
attributed to variations in temporal scopes, variable selections, geographical contexts,
and statistical approaches employed.
3.2.9 Oil Electricity (Variable X9) and Gas Electricity (Variable X10)
The oil electricity per capita variable represents the quantity of electricity generated
from oil per person measured in kilo-watt hour (KWH) per annum. In the same vein,
the gas electricity per capita variable represents the quantity of electricity generated
from gas per person measured in KiloWatt Hour (KWH) per annum.
A strong correlation between economic performance and electricity usage suggests
that the economy can only grow by the pace at which electricity production grows
(Hirsh & Koomey, 2015).
Figure 3.1 below shows that there is a relationship between GDP growth rate and
electricity demand growth. We therefore seek to know the contribution of two main
sources of electricity (oil and gas) to the economic development of the country groups
to inform rational policy decisions of these nations.
Figure 4: World GDP and Electricity Demand Growth Rates
Source: International Energy Agency, 2020
41
In summary, the above-identified variables (dependent and independent) will be
analysed to show the nature of their relationship vis-à-vis the economic development
of nations across the three broad nations categories: developed, developing, and least
developed nations.
3.3 Data Collection And Presentation
3.3.1. Type of Data
This study employed secondary data. Most secondary data are sourced from surveys,
observations, questionnaires, and governmental, intergovernmental, and
nongovernmental organizations (Womack, 2023). The study relied on historical time
series data obtained from the World Bank, UNCOMTRADE, UNDATA, World
Economic Situation and Prospects, and OECD databases, since it seeks to analyse the
economic implications of international energy trade.
3.3.2 The Scope and Frequency of Data
The data for this study covers the period 1995 to 2021 for all countries under the three
broad categories of nations namely developed, developing, and least developed on an
annual basis.
3.4 The Research Model
To understand the concept and application of panel regression, it is imperative to briefly
discuss the features of panel data which is used in running a panel regression.
3.4.1 Overview of Panel Data
Panel data, often known as longitudinal data, is a type of data consisting of multiple
time series observations by measuring the same variables on the same unit multiple
times (Brüderl et al., 2019). Thus, it involves using at least two dimensions of
observation. For example a cross-sectional dimension denoted by ‘i’ and a time series
dimension denoted by ‘t’. It may further exhibit a more intricate hierarchical or
clustering structure such that a variable could be the readings of air quality at a location
‘j’, of country ‘i’, at a time ‘t’ (McManus, 2011). Panel data is one of the three basic
42
categories of longitudinal data together with time series data and pooled crosssectional
data.
Time series data involves many observations (large t) made on even a single unit or
entity (small N). Examples are stock price trends and aggregate national statistics
(McManus, 2011).
Pooled cross-sectional data is when two or more independent observations of several
units (large N) are taken from the same population at varying times such as general
social surveys and population surveys (McManus, 2011).
Panel data entails more than one observation ‘j’, taken from many ‘i’ entities (large
N) at a time ‘t’ such as panel surveys of households and individuals, data on different
organisations and firms at varying times, time-aggregated regional data (McManus,
2011)
3.4.2 The Panel Data Notation
In panel data involving observations on ‘N’ entities over ‘T’ time periods,
measurements are taken from each of ‘N’ entities (subjects) ‘T’ a number of times.
These entities could be institutions, persons, businesses, nations, etc. Some variables
in the panel may change over time for t = 1,..., T, but others such as a person's gender,
a company's location, or a person's ethnicity, may remain constant (Fingleton, nd). A
panel data is deemed to be in balance if and only if there are no gaps or missing values
or data in between them. Hence, we have unbalanced panel data if ‘N’ and ‘T’
observations do not match or they contain missing data/values. Usually, ‘N’ is bigger
in relation to ‘T’ but not always (Fingleton, nd).
In panel data, given that Y denotes the dependent variable and X denotes the
independent variable, the following notations suffice: Yit = dependent variable value
for entity i at time t
X1it = Independent variable 1 value for entity i at time t
X2it = Independent variable 2 value for entity i at time t
…
…
XKit = Independent variable K value for entity i at time t.
43
In summary, the table below shows the presentation of panel data for two time periods.
Table 2: Panel Data Outlay
Source: (Brüderl et al., 2019)
Notably, cross-sectional data comprises of observations on ‘n’ subjects (N-entities),
while panel data has observations on ‘n’ entities at T ≥ 2 time periods indicated as (Xit,
Yit), for i = 1, . . . , n and t = 1, . . . , T where the index ‘i’ denotes the entity (subject)
and ‘t’ refers to the period (Hanck et al., 2023).
3.5 Overview Of Panel Regression Model
Panel regression analyses multiple observations of a group of independent variables
on multiple observations of one or more dependent variables (Hanck et al., 2023). For
this study, unbalanced panel data involving N cross-sectional units, i = 1,... , N, over
T periods, t = 1,... , T will be used.
To develop the panel model, we adopted the following connotations:
Yit represents the dependent variable Gross Domestic Product per capita of the country
i over time t.
X1it represents the crude oil production per capita of country i over time t
X2it represents the crude oil export value per capita of country i over time t
X3it represents the crude oil import value per capita of country i over time t
X4it represents the other petroleum products export value per capita (excluding crude
oil) of country i over time t.
44
X5it represents the other petroleum products' import value per capita (excluding crude
oil) of country i over time t.
X6it represents the natural gas export value per capita of a country i over time t.
X7it represents natural gas import value per capita of a country i over time t.
X8it represents the total energy use per capita of a country i over time t.
X9it represents oil electricity per capita of a country i over time t.
X10it represents gas electricity per capita of a country i over time t.
Thus, using generalised least squares to estimate the regression parameters, α and β,
the prospective panel regression model could be presented in the form:
Yit = αi + β1it X1it + β2it X2it + β3it X3it + β4it X4it + β5it X5it + β6it X6it + β7it X7it + β8it X8it +
β9it X9it + β10it X10it + µit
Where i = 1, 2, …, N t = 1, 2, …, T µit = the error term associated with the estimation
of the regression parameters.
Another way of presenting the panel regression model is the vector form viz:
Yi,t1 = X’I,t1 βt1 + µi,t1
Yi,t2 = X’I,t2 βt2 + µi,t2
…
…
…
Yi,T = X’I,T βT + µi,T
T = 1,2,…, T
We can say that
Yi = Xi β + µi
Where Yi = Yi,t1, Yi,t2, …, Yi,T
3.5.1. The Objective of Analysing a Panel Data
Panel data analysis is a statistical method employed to examine the dynamics of
variables or factors over time (Hanck et al., 2023). It is utilised to obtain more accurate
45
estimations of trends in social phenomena, establish causal models, or determine the
nature of relationships between multiple variables. This approach involves observing
and analysing data from multiple individuals or entities over an extended period.
(Hanck et al., 2023), thus, it is appropriate in analysing the economic implications of
international energy trade across the three categories of nations.
An illustrative instance of panel data is a collection of academic performance data for
a group of students across multiple courses over a specified duration for analysis.
Another instance that pertains to panel data analysis is a study consisting of aggregate
information on 128 countries over a span of 30 years to examine the impact of
democracy on human capital and economic growth (Hanck et al. 2023).
In the context of this research, the panel data typically consists of the Gross Domestic
Products (GDPs) of the three categories of nations namely developed, developing, and
least developed), observed over a specific period. Similarly, the compilation of crude
oil export values from various countries within the categories under investigation from
1995 to 2021 effectively represents a comprehensive panel data set. The
aforementioned principle applies to all other variables being examined in the study.
We must note that panel datasets have the potential to incorporate additional variables
that may vary over time or remain constant. This implies that the measurement of the
panel data is not inherently subject to temporal variation. In other words, a collection
of panel data can be acquired at a consistent interval, such as within a specific year or
any other designated time frame.
The utilisation of a suitable panel regression model on a collection of panel data can
yield results that have the potential to establish a causal connection between variables
that are observed repeatedly over time. This study focuses on investigating the
economic implications of international energy trade in particular, crude oil and natural
gas energy in developed, developing, and least developed countries using a panel
regression approach.
46
3.5.2 Advantages of panel regression
Panel data which combines inter-individual differences and intra-individual dynamics,
offers several advantages compared to cross-sectional or time-series data (Hsiao,
2006), as stated below.
i. Panel data analysis enables the identification of causal effects with less
stringent assumptions, in comparison to the utilisation of cross-sectional data.
It makes it possible to ascertain the temporal sequence of events, thereby
enabling the examination of the impact of an event on the outcome (Brüderl et
al., 2019).
ii. It enables the examination of individual trajectories, specifically individual
growth curves about various factors such as wage, materialism, and
intelligence. Within this context, it is possible to differentiate between group
effects and age effects. - The process of transitioning into and out of states,
such as poverty (Brüderl et al., 2019).
iii. Panel data typically possess a greater number of degrees of freedom and
exhibit more sample variability which provides more accurate inference of
model parameters compared to cross-sectional data (Hsiao, 2006).
iv. Regression analysis with panel data can help address the issue of omitted
variable bias in situations by incorporating intertemporal dynamics and
individual characteristics (Hsiao, 2006) where there is a lack of information
on variables that are correlated with both the independent variables of interest
and the dependent variable. (Hanck et al., 2023).
v. The act of pooling data to generate predictions for individual outcomes is more
likely to result in accurate predictions compared to generating predictions
solely based on the data of the individual in question (Hsiao, 2006).
vi. Panel data analysis typically encompasses two dimensions, namely a
crosssectional dimension and a time series dimension. Characteristically, the
computation of panel data estimators or inference is anticipated to be more
intricate compared to cross-sectional or time series data, assuming normal
conditions. Nevertheless, in specific instances, the presence of panel data can
facilitate computation and inference as presented in the following examples:
47
a. Analysis of nonstationary time series: If time series data exhibit
nonstationarity, the normal distribution assumption for the least-
squares or maximum likelihood estimators' large sample
approximations no longer holds. However, in the presence of panel data
and independent observations among cross-sectional units, it is
possible to utilise the central limit theorem to demonstrate that the
asymptotic normality of various estimators persists (Hsiao, 2006).
b. Measurement errors: Measurement errors have the potential to result in
the under-identification of an econometric model, as demonstrated by
Aigner et al. (1984) having access to multiple observations for a
particular individual or at a specific time can provide researchers with
the opportunity to apply various transformations.
Panel regression techniques can be utilised to enhance multiple regression models
when panel data is available. This is due to the possibility that findings from multiple
regression models might be invalid (Hanck et al., 2023). However, it allows for the
examination of causal relationships between multiple variables, such as the association
between GDP and international trade in crude oil, across different categories of
countries over a specific time frame. The application of linear or multiple regression
analysis to the aforementioned phenomenon may present challenges, intricacies, or
potential limitations due to the inclusion of three observational dimensions, namely
the GDP of entities categorised over a specified time frame.
3.6 Research Design
The research design characteristically outlines the steps taken to answer the research
questions which bother on the nature of the relationship between GDP and
international trade of crude oil and natural gas across country groupings. The research
also sought to establish the energy trade patterns their effect on the GDP of country
categories.
To achieve this, relevant variables were identified (dependent and independent), and
data was collected. The data were thereafter organised in panels according to the
categories suitable for the panel regression approach.
48
The research hypothesis is such that:
i. H0: The regression coefficients are not significant (H0 : βi = 0 ) for P-value greater
than 5% ii. H1: The regression coefficients are significant (H1 : βi ≠ 0) for p-values
less than 5%
3.6.1 Level of significance (Critical Level)
The chosen level of significance for this study is 5%. This means that the study tolerates
a maximum of 5% chance events under the research hypothesis.
3.6.2 The Panel Regression Models
Given that there are three country classifications/categories under consideration
(developed, developing, and least developed), three models are expected from this
research as follows:
a. Model for the relationship between GDP per capita and international energy
(crude oil and natural gas) trade in the developed countries category.
b. Model for the relationship between GDP per capita and international energy
(crude oil and natural gas) trade in the developing countries category
c. Model for the relationship between GDP per capita and international energy
(crude oil and natural gas) trade in the least developed countries category
The models will be used to establish trends in the international energy trade (crude oil
and natural gas) to provide a comparative analysis across country classifications.
3.6.3 Descriptive Statistics
In this study, the initial statistical analysis will include measures of central tendency
(such as mean, mode, and median), deviations from the mean (standard deviation and
variance), measures of deviation from normality (skewness and kurtosis), and the
range of values (maximum and minimum) for all variables (George & Mallery, 2016).
49
3.6.4 Test for Multicollinearity
A multi-collinearity test will be employed to detect and eliminate any instances where
two or more independent variables exhibit a high degree of correlation. Based on sound
economic rationale and careful consideration of trade-offs, it is deemed necessary to
eliminate one of the variables from the model due to its correlation exceeding 80%.
The calculation of correlation between two variables X and Y, based on a sample size
of n, is expressed as:
3.6.5 T-Test for regression coefficients
The t-test will be employed to determine the statistical significance of the independent
factors in impacting the dependent variable. Additionally, it will show the degree to
which the independent factors influence the dependent variable.
The research hypothesis is:
H0: The regression coefficients are not significant (H0 : β = 0 ) for P-value
greater than 5%
H1: The regression coefficients are significant (H1 : β ≠ 0) for p-values less than
5%
50
Chapter 4 - Data Analysis And Findings
In keeping with the research structure elucidated in chapter one, this chapter focuses
on statistical analysis of the secondary data obtained. The identified dependent and
independent variables are presented below.
Table 3: Identified Variables
Variable
Variable Description
Status
Y
Gross Domestic Product Per
Capita
Dependent Variable
X1
Crude Oil Production Per
Capita
Independent Variable
X2
Crude Oil Export Per Capita
Independent Variable
X3
Crude Oil Import Per Capita
Independent Variable
X4
Other Petroleum Products
Export Per Capita
Independent Variable
X5
Other Petroleum Products
Import Per Capita
Independent Variable
X6
Natural Gas Export Per
Capita
Independent Variable
X7
Natural Gas Import Per
Capita
Independent Variable
X8
Total Energy Use Per
Capita
Independent Variable
X9
Oil Electricity Per Capita
Independent Variable
X10
Gas Electricity Per Capita
Independent Variable
4.1. Preliminary Statistics
A descriptive analysis was carried out on the quantitative data to provide an overview
of its characteristics before the regression analysis. These include the measure of
central tendency and dispersion from the mean, skewness and kurtosis, minimum and
maximum values, and data count. Line graphs were also used to show how the time
series data behaved during the period under study (1995-2021). The graphs are
presented in appendixes 1 – 3 according to the country classifications.
The central tendency was determined by utilising the mean of each variable (to
represent the average of the data points) as well as the standard deviation which
51
measured the dispersion of values and their associations with the mean values.
Additional statistical measures, such as skewness and kurtosis, were computed to assess
the extent of sample deviations from normality.
Furthermore, the maximum and minimum values were determined to quantify the range
of the data.
Details of the preliminary statistics for all country categories are presented in Tables
4.2, 4.3, and 4.4.
Table 4: Preliminary Statistics for Developed Countries
Y
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
Mean
32,135.94
249.41
285,546.31
401,606.84
383,888.11
726,281.86
16,996.12
19,415.92
51,437.93
717.99
1,087.01
Standard
Error
716.41
24.00
41,514.67
16,860.15
19,915.50
48,237.21
3,265.06
1,745.66
926.45
45.52
36.71
Median
27,824.47
-
2,197.99
271,699.86
166,738.22
255,645.79
5.10
89.36
44,694.92
265.52
694.27
Standard
Deviation
22,335.45
748.17
1,294,299.46
525,647.58
620,903.73
1,503,887.38
101,794.57
54,424.42
28,883.73
1,411.96
1,138.72
Sample
Variance
4.99E+08
5.60E+0
5
1.68E+12
2.76E+11
3.86E+11
2.26E+12
1.04E+10
2.96E+09
8.34E+08
1.99E+0
6
1.30E+0
6
Kurtosis
2.17
16.67
47.65
23.10
18.19
41.60
104.40
33.78
4.30
12.30
3.16
Skewness
1.24
3.97
6.62
4.06
3.71
5.63
9.44
5.09
1.83
3.45
1.58
Range
132,385.1
2
5,195.15
13,743,396.1
9
4,995,478.2
6
5,395,846.6
5
16,706,041.3
6
1,447,855.6
1
561,401.1
3
172,514.0
2
9,066.87
6,880.76
Minimu
m
1,360.28
0.00
0.00
0.00
0.00
0.00
0.00
0.00
15779.98
0.00
0.00
Maximu
m
133,745.4
0
5,195.15
13,743,396.1
9
4,995,478.2
6
5,395,846.6
5
16,706,041.3
6
1,447,855.6
1
561,401.1
3
188,294.0
0
9,066.87
6,880.76
Sum
3.12E+07
2.42E+0
5
2.78E+08
3.90E+08
3.73E+08
7.06E+08
1.65E+07
1.89E+07
5.00E+07
6.91E+0
5
1.05E+0
6
Count
972.00
972.00
972.00
972.00
972.00
972.00
972.00
972.00
972.00
962.00
962.00
Source: Created by the Authors
Table 4 above summarizes the data for developed nations. The variable with the
highest mean value was X5 with 726,281.86 while the variable with the lowest mean
value was X1 with 249.41. the variable that showed the highest standard deviation
from the mean within this classification was also X5 with 1,503,887 while the one with
the least standard deviation was X10 with 1,138.72. unequal observation count was
also seen indicating that the panel data is an unbalanced one with missing values which
a panel regression technique addresses. The highest data point within this category was
16,706,041.36 found in X5 while the minimum value of 0.00 was found across X1,
X2, X3, X4, X5, X6, X7, X9, X10. This means that within this classification, only the
variable X8 had a non-zero observation on all entities.
52
53
5: Preliminary Statistics for Developing Countries
Y
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
Mean
8,368.36
6,891.87
688,674.93
173,549.99
344,567.21
375,510.07
225,867.50
12,104.8
8
26,887.1
8
541.10
1,557.06
Standard
Error
281.44
919.69
53,643.99
16,382.19
28,378.69
28,290.27
42,818.68
1,413.40
979.16
25.45
96.78
Median
4,189.35
30.71
9,603.53
1,111.14
16,855.80
70,351.05
0.00
1.15
12,559.7
7
195.80
145.56
Standar
d
Deviatio
n
11,648.3
3
38,230.8
3
2,229,938.7
9
680,994.68
1,179,680.1
7
1,176,004.5
3
1,779,938.9
0
58,753.8
7
40,703.0
4
979.77
3,726.92
Sample
Variance
1.36E+
08
1.46E+09
4.97E+12
4.64E+11
1.39E+12
1.38E+12
3.17E+12
3.45E+09
1.66E+09
9.60E+0
5
1.39E+
07
Kurtosis
13.92
63.48
33.69
53.69
46.22
50.33
187.39
72.42
9.80
9.75
12.60
Skewness
3.25
7.92
5.28
6.71
6.09
6.54
12.73
7.78
3.02
3.07
3.57
Range
97,941.6
0
386,491.
51
21,764,172.
87
8,154,477.
72
14,214,268.
43
12,754,718.
91
32,475,762.
17
845,470.
91
301,937.
98
5,731.4
1
21,704.8
7
Minimu
m
99.76
0.00
0.00
0.00
0.00
0.00
0.00
0.00
875.42
0.00
0.00
Maximu
m
98,041.3
6
386,491.
51
21,764,172.
87
8,154,477.
72
14,214,268.
43
12,754,718.
91
32,475,762.
17
845,470.
91
302,813.
40
5,731.4
1
21,704.8
7
Sum
1.43E+
07
1.19E+07
1.19E+09
3.00E+08
5.95E+08
6.49E+08
3.90E+08
2.09E+07
4.65E+07
8.02E+0
5
2.31E+
06
Count
1,713.00
1,728.00
1,728.00
1,728.00
1,728.00
1,728.00
1,728.00
1,728.00
1,728.00
1,482.0
0
1,483.00
Source: Created by the Authors
Table 5 above shows that the variables with the highest and lowest means values within
the developing nations classification are X2 and X9 respectively while the variables
with the highest and lowest standard deviations are X6 and X9 with 1,779,938.90 and
979.77 respectively. The large gap between these measures of central tendency
indicates how diverse patterns of energy trade within this classification can be. Also,
the unequal data points/observations show that the panel data is unbalanced one due
to missing values. The maximum data point was found in X6 while the lowest data
point is 0.00 found in X1, X2, X3, X4, X5, X6, X7, X9, X10. Again, the gap between
the highest and the lowest observations indicates how varied the energy trade among
this country classification was within the timeframe of the study. However, the panel
regression analysis will reveal in detail, the level and nature of international energy
trade of this country group.
Table 6: Preliminary Statistics for Least Developed Countries
Table
54
Y
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
Mean
8.49E+0
2
6.77E+0
3
7.60E+06
7.39E+05
1.29E+06
1.82E+07
3.30E+05
3.62E+04
1.81E+0
3
5.86E+0
1
7.75E+0
0
Standard
Error
21.03
1,679.83
2,128,904.3
8
191,716.1
8
248,978.4
4
2,814,250.5
1
141,913.1
5
16,520.0
0
92.52
2.46
1.09
Median
628.95
0.00
0.00
0.00
0.19
20.49
0.00
0.00
922.82
26.40
0.00
Standard
Deviation
7.33E+0
2
5.92E+0
4
7.50E+07
6.76E+06
8.77E+06
9.92E+07
5.00E+06
5.82E+05
3.20E+0
3
7.62E+0
1
3.38E+0
1
Sample
Variance
5.38E+0
5
3.50E+0
9
5.63E+15
4.56E+13
7.70E+13
9.84E+15
2.50E+13
3.39E+11
1.03E+0
7
5.80E+0
3
1.14E+0
3
Kurtosis
8.43
109.64
790.40
310.30
186.55
72.37
297.30
872.04
33.02
4.60
51.58
Skewness
2.47
10.20
25.80
16.14
12.18
7.93
16.86
27.85
5.39
2.04
6.60
Range
5.28E+0
3
7.77E+0
5
2.37E+09
1.46E+08
1.74E+08
1.22E+09
1.01E+08
1.88E+07
2.78E+0
4
4.22E+0
2
3.60E+0
2
Minimum
86.79
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Maximu
m
5.37E+0
3
7.77E+0
5
2.37E+09
1.46E+08
1.74E+08
1.22E+09
1.01E+08
1.88E+07
2.78E+0
4
4.22E+0
2
3.60E+0
2
Sum
1.03E+0
6
8.40E+0
6
9.44E+09
9.18E+08
1.60E+09
2.26E+10
4.10E+08
4.50E+07
2.17E+0
6
5.60E+0
4
7.41E+0
3
Count
1,216.00
1,242.00
1,242.00
1,242.00
1,242.00
1,242.00
1,242.00
1,242.00
1,198.00
956.00
956.00
Source: Created by the Authors
Within the LCDs, the variables with the highest and lowest mean values were X5 and
X10 respectively with 18,229,178.14 and 7.75. The variables with the highest and
lowest standard deviations were X5 and X10 with 99,179,873.86 and 33.78
respectively. The maximum data point was found in X5 with 1,222,366,313.85 while
the lowest data point is 0.00 found in all the variables.
In conclusion, the descriptive statistics as seen in the three classifications suggest that
that energy trade significantly varies across country classifications. However,
variations will be revealed in detail by the panel regression analysis both in terms of
nature and magnitude.
4.2. Test for Multicollinearity
To conduct a regression of the dependent variable on the independent variables, a
multicollinearity (correlation of independent variables) test was conducted within each
country category. The outcomes are presented in the subsequent subsections.
55
4.2.1. Multicollinearity Test for the Developed Countries’ Category
A correlation test conducted for developed countries’ independent variables dataset
revealed that they were all uncorrelated. This indicates that there is no statistically
significant association or influence between any of the independent variables and one
or more of the other independent variables. Consequently, the correlation results as
presented in Table 7 satisfied an important condition for regressing a dependent
variable on a set of independent variables.
7: Correlation Coefficients for the Developed Countries
Source: Created by the Authors
4.2.2. Multicollinearity Test for the Developing Countries’ Category.
After conducting a correlation analysis on the independent variables within the
category of developing countries, it was found that there was an 80% correlation
between variable X8 -(total energy use per capita) and variable X10 - (gas electricity
per capita). The output is presented in Table 4.6 below.
Table
56
Table 8: Correlation Coefficient for Developing Countries
Source: Created by the Authors
To rectify the anomaly of multicollinearity of the two variables, the variable
representing "gas electricity per capita” was excluded from the set of variables for the
developing countries, while the variable representing total energy use per capita was
retained.
The rationale for this decision was based on the fact that total energy use per capita
encompasses various sources such as coal, oil, wind, and hydropower, including gas
and electricity. Thus, given that the focus of this research borders on the international
trade of energy, it is interesting to reveal and understand how energy use per capita
influences the per capita GDPs of developing countries. If found to be significant, the
research findings will contribute to the formulation or reinforcement of public policies
on energy investment and use in the developing countries.
The final variable set for the developing countries category after the removal of one of
the correlated variables (gas electricity per capita) is presented in Table 9 below.
Table 9: Final Variables Set for Developing Countries
Variable
Variable Description
Status
Y
Gross Domestic Product Per Capita
Dependent Variable
X1
Crude Oil Production Per Capita
Independent Variable
X2
Crude Oil Export Per Capita
Independent Variable
X3
Crude Oil Import Per Capita
Independent Variable
57
X4
Other Petroleum Products Export Per Capita
Independent Variable
X5
Other Petroleum Products Import Per Capita
Independent Variable
X6
Natural Gas Export Per Capita
Independent Variable
X7
Natural Gas Import Per Capita
Independent Variable
X8
Total Energy Use Per Capita
Independent Variable
X9
Oil Electricity Per Capita
Independent Variable
4.2.3. Multicollinearity Test for the Least Developed Countries’ Category
The correlation test conducted on the set of independent variables for the Least
Developed Countries category indicated that there was no statistically significant
correlation between the variables. This shows that none of the independent variables
influences the other or co-vary with as much as 80%, hence satisfying an important
condition for regressing the dependent variable (per capita GDP) on the independent
variables as presented in Table 10 below.
10: Correlation Coefficient Table for Least Developed Countries
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X1
1
X2
0.00
1
X3
-0.01
0.00
1
X4
-0.01
0.10
0.70
1
X5
-0.02
0.09
0.27
0.42
1
X6
-0.01
0.12
-0.01
0.14
0.03
1
X7
-0.01
0.00
-0.01
0.00
0.33
0.00
1
X8
0.01
0.00
0.01
0.00
-0.07
0.03
-0.03
1
X9
0.00
0.19
-0.03
0.05
-0.02
0.14
0.01
0.06
1
X10
0.05
0.02
-0.02
-0.01
-0.02
0.11
-0.03
0.02
0.09
1
Source: Created by the Authors.
Table
58
4.3 Regression Analysis
According to the research design, panel regression analysis was carried out for the
panel dataset for the three categories of countries. MATLAB application software was
used to analyse the datasets to show the cause-effect relationship between the
dependent variable (per capita GDP) and the independent variables. The following
sections contain the three-panel regression models output and interpretations.
4.3.1 Model 1: Regression Model for the per capita GDP of Developed Countries.
Table 11: Panel Regression Analysis Output for Developed Countries
Table of Coefficients for Regression 1 (Developed Countries)
Variables (per Capita)
Parameter
Estimate
Standard
Error (SE)
Test Statistic
(tStat)
Probability
Value
(pValue)
Conclusion
Intercept
9194.70
1283.9
7.1617
1.59E-12
Significant
X1 (Crude Oil Production)
-1.4175
0.77133
-1.8378
0.066409
Not Significant
X2 (Crude Oil Export)
0.0044839
0.00049127
9.1271
4.12E-19
Significant
X3 (Crude Oil Import)
0.0088036
0.0014103
6.2425
6.48E-10
Significant
X4 (Other Petroleum Products Export)
-0.009422
0.0014862
-6.3395
3.55E-10
Significant
X5 (Other Petroleum Products Import)
0.0040507
0.00051655
7.842
1.19E-14
Significant
X6 (Natural Gas Export)
0.023104
0.005333
4.3323
1.63E-05
Significant
X7 (Natural Gas Import)
-0.0017954
0.010388
-0.17283
0.86282
Not Significant
59
X8 (Total Energy Used)
0.279
0.021781
12.809
9.08E-35
Significant
X9 (Oil Electricity)
-1.3573
0.41557
-3.2662
0.001129
Significant
X10 (Gas Electricity)
4.9816
0.55023
9.0536
7.66E-19
Significant
Number of Observations
962
Error Degree of Freedom
951
Root Mean Squared Error
1.65E+04
R-Square
46.50%
R-Square Adjusted
46.00%
Level of Significance
5.00%
At 5% level of significance (critical level), the output of the panel regression of the
dependent variable Y (Gross Domestic Product per Capita) on ten independent
variables for the Developed Country category showed that eight variables including
X2 -Crude Oil Export Per Capita, X3- Crude Oil Import per Capita, X4-Other Petroleum
Products Export Per Capita, X5-Other Petroleum Products Import Per Capita,
X6Natural Gas Export Per Capita, X8-Total Energy Used Per Capita, Oil Electricity
Per Capita, and Gas Electricity Per Capita were statistically significant in influencing
the per capita GDPs of the developed countries. On the other hand, two variables
X1(Crude Oil Production per capita) and X7 (Natural Gas Import per Capita) were
found to have no significant impact on the per capita GDPs of the Developed
Countries. The analysis also demonstrated that the adjusted coefficient of
determination, R2 is 46%, indicating that the significant variables jointly account for
about 46% of the variations in the per capita GDP of developed nations within the
limits of this study. The unexplained variations may be ascribed to potential sources
of observation error, such as qualitative and quantitative factors which were not taken
into consideration in
60
this study. Additionally, limitations as discussed in Chapter One, may have contributed
to these differences.
Accordingly, the regression model (Regression 1) of the per capita GDPs of the
Developed Countries is presented below.
Model 1:
Y = 9,194.70 + 0.0044839X2 + 0.0088036X3 – 0.009422X4 + 0.0040507X5 +
0.023104X6 + 0.279X8 – 1.3575X9 + 4.9816X10 + ui
Below is the presentation of the regression output for each of the variables.
X1 - Crude Oil Production.
The regression analysis output revealed that crude oil production did not exhibit
statistical significance, indicating that it does not have a discernible effect on the per
capita GDPs of developed nations. This suggests that there is no statistically significant
relationship between the per capita GDPs of developed nations and the value of crude
oil output per capita.
X2 - Crude Oil Export Per Capita
Crude Oil Export was significant and positive on the per capita GDPs of Developed
Nations. This means that a unit increase in per capita crude oil export of developed
countries will lead to 0.0044839 units increase in their per capita GDP, provided other
variables are held constant. In other words, for every 1% increase in the per capita oil
export variable, there will be a corresponding 0.4484% increase in the per capita GDPs
of the developed nations, when all other variables are fixed.
X3 - Crude Oil Import Per Capita
Crude oil import per capita was significant and positive for the developed countries
group. This implies that a unit increase in per capita crude oil export value will result
in 0.0088036 unit increase in the per capita GDPs of developed countries, when all
other variables are constant. Put differently, for each 1% rise in per capita crude oil
import variable, there will be a corresponding 0.8804% increase in the per capita GDPs
of the developed nations, provided that all other variables are kept constant
61
X4 - Other Petroleum Product Export (Excluding crude oil)
The variable - other petroleum products export per capita was significant but negative
for the Developed Countries. This shows that, if all other variables are held constant,
a unit increase in other petroleum products export value will result in a 0.009422
decrease in the per capita GDPs of the developed countries. This also means that for
every 1% increase in per capita export of other petroleum products variable, there will
be a resultant 0.9422% decrease in the per capita GDPs of the developed nations, if all
other variables are kept constant.
X5 - Other Petroleum Product Import per Capita (Excluding crude oil) The
importation of other petroleum products into the developed countries proved
significant and positively affects their GDPs per Capita. Accordingly, a one-unit
increase in the value of other petroleum products imported into the developed
countries results in an increase in their per capita GDP by 0.0040507 units, if all other
variables are held constant. Thus, for every 1% increase in the import value of other
petroleum products, there will be a corresponding 0.4051% increase in the per capita
GDPs of developed nations, all other variables remaining constant.
X6 Natural Gas Export Per Capita
The Natural Gas Export per capita variable was found significant and positive in
explaining changes in the per capita GDPs of developed countries. Thus, a unit
increase in the value of Natural Gas exports per capita will result in a 0.023104 units
increase in the per capita GDPs of developed countries if all the other variables are
kept constant. In effect, for every 1% increase in natural gas export value, there will
be an associated 2.3104% increase in the per capita GDPs of developed nations.
X7 Natural Gas Import Per Capita
The natural gas import per capita variable was not significant in explaining the changes
in the per capita GDPs of developed nations within the scope of this study. This means
that the values expended to import natural gas in the developed nations are of no
statistical significance on their per capita GDPs.
62
X8 - Total Energy Used Per Capita
The total energy used per capita was significant and positive at a 5% critical level. This
implies that a unit increase in per capita energy consumption (KWH) will result in a
0.279 increase in the per capita GDPs of developed nations if all other variables are
kept constant. Accordingly, for every 1% increase in the total energy use per capita,
there will be a corresponding 27.9% increase in the per capita GDPs of developed
nations if all other variables are held constant.
X9 (Oil Electricity Per Capita)
The Per Capita Oil Electricity variable was significant but negative. This means that a
unit increase in the electricity generated from crude oil will result in a 1.3575 units
decrease in the per capita GDPs of the developed countries. In other words, a 1%
increase in per capita oil electricity will result in a 135.75% decline in the per capita
GDPs of developed nations, as long as other variables are kept constant.
X10 (Gas Electricity Per Capita)
Gas electricity was both significant and positive in the model indicating that it
positively influences the per capita GDP of developed nations. Hence, provided all
other variables are kept constant, a unit increase in the gas electricity generated per
capita will result in a 4.9816 unit increase in the per capita GDPs of the developed
nations. Hence, for every 1% increase in gas electricity generation per capita, there
will be an accompanying 498.16% increase in the per capita GDPs of developed
nations.
63
4.3.2 Model 2: Regression Model for the GDP of Developing Countries Category
Table 12: Panel Regression Analysis Output for Developing Countries
Table of Coefficients for Regression 2 (Developing Countries)
Variables
Parameter
Estimate
Standard
Error (SE)
Test Statistic
(tStat)
Probability
Value
(pValue)
Conclusion
Intercept
2557.8
211.37
12.101
3.44E-32
Significant
X1 (Crude oil Production)
-0.0058739
0.0038996
-1.5063
0.13221
Not significant
X2 (Crude oil Export)
0.001104
9.47E-05
11.663
4.07E-30
Significant
X3 (Crude oil Import)
-0.0003036
0.0003435
-0.88388
0.3769
Not significant
X4 (Other Petroleum product Export)
-0.0006198
0.00027374
-2.2641
0.023714
Significant
X5 (Other Petroleum product Import)
0.0031679
0.00023569
13.441
6.53E-39
Significant
X6 (Natural Gas Export)
0.001656
0.00010368
15.972
4.81E-53
Significant
X7 (Natural Gas Import)
0.030472
0.0028024
10.874
1.56E-26
Significant
X8 (Total Energy Used)
0.12428
0.0067165
18.504
7.84E-69
Significant
X9 (Oil Electricity)
0.57904
0.18616
3.1104
0.0019045
Significant
Number of Observations
1468
Error Degree of Freedom
1458
Root Mean Squared Error
5.88E+03
R-Square
76.90%
R-Square Adjusted
76.70%
Level of Significance
5.00%
At 5% critical level, the panel regression of Y - (Gross Domestic Product per Capita)
on nine independent variables for the Developing Country category showed that eight
variables including X2 - (Crude Oil Export Per Capita), X4 – (Other Petroleum Products
Export Per Capita), X5 (Other Petroleum Product Import per Capita), X6 (Natural Gas
Export per Capita), X7 (Natural Gas Import per Capita), X8 (Total Energy Used Per
Capita), X9 (Oil Electricity Per Capita), and X10 (Gas Electricity Per Capita) were
statistically significant in influencing the per capita GDPs of developing countries. On
the other hand, X1 - (Crude Oil Production Per Capita), and X3 – Crude Oil Import Per
Capita) were found to be insignificant in explaining changes in the GDPs of the
Developing Countries.
64
The analysis also revealed that the adjusted coefficient of determination, R2 is 76.70%
signifying that all the significant variables collectively explain about 76.70% of the
changes in the GDP of developing countries within the scope of this research. The
unexplained variations could be attributed to observation error-like variables
(qualitative and quantitative) that were not considered in this study, as well as other
limitations as highlighted in Chapter One.
Therefore, the regression model (Regression 2) for the GDPs of the Developing
Countries Group is presented below.
Y = 2,557.8 + 0.001104X2 – 0.00061977X4 + 0.0031679X5 + 0.001656X6 + 0.030472X7
+ 0.12428X8 + 0.57904 X9 + ui
Below is a detailed analysis of the variable contribution to the GDP of the Developing
Countries category.
X1 - (Crude Oil Production per Capita)
Per capita crude oil production value was not significant for the developing countries.
This implies that the value of crude oil production per capita does not have any
statistically proven effect on the per capita GDPs of Developing Nations. This also
means that, in relation to the per capita GDPs of the Developing Nations, the value of
per capita crude oil production is very small or negligible to cause a significant effect.
X2 - (Crude Oil Export Per Capita)
The crude oil export per capita variable was significant and positive for Developing
Countries. This means that a unit increase in the value of per capita crude oil export in
the developing nations will result in 0.001104 units increase in their per capita GDPs,
if all other variables are held constant. It also implies that for every 1% increase in
crude oil export value per capita, there will be a corresponding 0.1104% increase in
the per capita GDPs of developing nations when all other variables are kept constant.
X3 - (Crude Oil Import per Capita)
The crude oil import per capita variable was insignificant for the per capita GDPs of
the developing countries. This indicates that the variable has no statistically proven
impact on the per capita GDPs of the developing country group.
65
X4 - (Other Petroleum Product Export per Capita)
The variable ‘other petroleum products per capita’ was significant but negative in
influencing the per capita GDPs of the developing countries. Accordingly, a unit
increase in the value of other petroleum products exported (excluding crude oil) will
result in 0.00061977 unit decrease in the per capita GDPs of the developing countries.
In other words, for every 1% increase in the export of other petroleum products, there
will be a corresponding 0.06198% decrease in the per capita GDPs of developing
nations, if all other variables are kept constant.
X5 - (Other Petroleum Product Import per Capita)
Other petroleum products proved significant and positive towards the per capita GDPs
of developing countries. This implies that an increase in the value of per capita
petroleum products importation by one unit will result in 0.0031679 unit increase in
the GDP per capita of this country group, provided all other variables remain
unchanged. Accordingly, for every 1% increase in the import of other petroleum
products, there will be an associated 0.3168% increase in the per capita GDPs of
developing nations, when all other variables are held constant.
X6 - (Natural Gas Export per Capita)
Natural Gas Export per Capita was significant and positively affects the GDP of
developing countries. In other words, a unit increase in the value of natural gas exports
from developing countries leads to an increase in their per capita GDP by 0.001656
units, if all other variables are held constant. Thus, every 1% rise in natural gas export
value will result in a 0.1656% increase in the per capita GDPs of developing nations
when all other variables are kept constant.
X7 - (Natural Gas Import per Capita)
Just like the natural gas export variable, the natural gas import per capita variable was
also significant and positive towards the per capita GDPs of developing countries
category. Thus, a unit increase in natural gas import value per capita increases the per
capita GDP per capita of the developing countries by 0.030472 when all the other
variables are fixed. This also means that a 1% increase in the import value of natural
66
gas will lead to a corresponding 3.0472% increase in the per capita GDPs of
developing nations.
X8 - Total Energy Used Per Capita
The total energy used per capita was significant and positive at a 5% critical level. This
indicates that for every one-unit increase in per capita energy consumption (KWH),
there will be a 0.12428 increase in the per capita GDPs of developing nations if all
other variables are kept constant. Thus, for every 1% rise in per capita energy use,
there will be a corresponding rise in the per capita GDPs of developing nations by
124.28%, if all other variables are kept constant. This outcome highlights that energy
use in developing countries leads to economic growth.
X9 - Oil Electricity Per Capita
The oil electricity per capita variable which represents the value of crude oil used to
generate electricity was found significant and positive towards the per capita GDPs of
the developing countries category. In other words, a unit increase in the electricity
generated from crude oil will result in a 0.57904 increase in the per capita GDP of
developing nations. That means that a 1% increase in the oil electricity per capita will
result in a 57.904% increase in the per capita GDPs of developing nations.
4.3.3 Model 3: Regression Model for the GDP of Least Developed Countries
Table 13: Panel Regression Analysis Output for Least Developed Nations
Table of Coefficients for Regression 3 (Least Developed Countries)
Variables (per Capita)
Parameter
Estimate
Standard
Error (SE)
Test Statistic
(tStat)
Probability
Value
(pValue)
Conclusion
Intercept
486.91
24.118
20.188
1.5571E-75
Significant
X1 (Crude Oil Production)
0.0013421
0.00036018
3.7263
0.00020596
Significant
X2 (Crude Oil Export)
-3.326E-07
0.00000065
-51094.00
0.60952
Not Significant
X3 (Crude Oil Import)
1.0833E-05
3.50120E-06
3.094
0.0020334
Significant
X4 (Other Petroleum Products Export)
-1.261E-05
4.06120E-06
-3.1059
0.0019544
Significant
X5 (Other Petroleum Products Import)
1.2622E-06
5.3286E-07
2.3688
0.018049
Significant
X6 (Natural Gas Export)
-1.702E-06
3.2469E-06
-5.5241
0.60033
Not Significant
X7 (Natural Gas Import)
-0.0003704
0.00056438
-0.6564
0.51176
Not Significant
X8 (Total Energy Used)
0.10361
0.0050317
20.5920
5.1455E-78
Significant
X9 (Oil Electricity)
2.9398
0.23233
12.6530
5.4198E-34
Significant
X10 (Gas Electricity)
2.2127
0.5142
4.3032
1.8607E-05
Significant
67
Number of Observations
948
Error Degree of Freedom
937
Root Mean Squared Error
5.31E+02
R-Square
41.80%
R-Square Adjusted
41.20%
Level of Significance
5.0%
From Table 13 above, at a 5% level of significance, the panel regression output of the
Y (Gross Domestic Product per Capita) on ten independent variables for the Least
Developed Country category showed that seven variables were statistically significant
towards the per capita GDPs of Least Developed Country. These significant variables
include: X1 – Crude Oil Production, X3 -(Crude Oil Import Per Capita), X4 - (Other
Petroleum Product Export per Capita), X5 - (Other Petroleum Product Import per
Capita), X8 - (Total Energy Used Per Capita), X9 - (Oil Electricity Per Capita), and X10
- (Gas Electricity Per Capita). Conversely, three variables including X3 - (Crude Oil
Export per Capita), X6 - (Natural Gas Export per Capita), and X7 - (Natural Gas Import
per Capita) were found insignificant in explaining variations in the GDP of the Least
Developed Countries.
The analysis further showed that the adjusted coefficient of determination, R-square is
41.20% indicating that, collectively, the significant variables only explain about
41.20% of the total variation in the GDPs of Least Developed Countries within the
scope of this research. The remaining unexplained variations could be attributed to
error and other variables (qualitative and quantitative) not considered in this study.
Accordingly, the regression model (Regression 3) of the per capita GDP of the Least
Developed Countries Group is presented below.
Y = 486.91 + 0.0013421X1 + 0.000010833X3 – 0.0000012614X4 + 0.00000012622X5 +
0.10361X8 + 2.9398X9 + 2.2127 + u
Below is the interpretation of the regression output for each of the variables.
68
X1 - Crude Oil Production Per Capita
Crude oil production per capita was significant towards the per capita GDPs of Least
Developed Nations. This implies that a unit increase in crude oil production value will
result in 0.0013421 unit increase in the per capita GDPs of Least Developed Nations,
provided all other variables are fixed. Put differently, for every 1% increase in the
value of crude oil produced in LDNs, there will be a 0.1342% increase in their per
capita GDPs if other variables are kept constant.
X2 - Crude Oil Export Per Capita
The crude oil export variable was not significant for the least developed countries. In
other words, the effect of per capita crude oil exports on the GDP per capita of the
least developed countries was insignificant. This indicates that the value of LDCs'
exports of crude oil has no demonstrable impact on their GDP per capita. Put
differently, the value of LDCs' per capita crude oil export is too low to have a
meaningful impact on those countries' GDPs.
X3 - Crude Oil Import Per Capita
The per capita crude oil imports variable exhibited a statistically significant and
positive impact on the per capita gross domestic product (GDPs) of the least developed
nations. Consequently, a marginal increase of one unit in crude oil imports per capita
in the least developed nations is associated with a corresponding rise of 0.000010833
units in their per capita GDP. To clarify, it might be said that a 1% rise in crude oil
import per capita is associated with a proportional increase of 0.00108% in the per
capita GDPs of the least developed nations.
X4 - Other Petroleum Product Export (Excluding crude oil)
Other petroleum products export variable was shown to be a statistically significant
variable. However, its effect on the per capita GDP of LDCs was negative. This means
that the per capita gross domestic product (GDP) of LDCs will decrease by
0.0000012614 units for every one-unit rise in the value of other petroleum products
exported. In other words, the per capita GDPs of LDCs will decline by 0.000126% for
every 1% increase in the export values of other petroleum products, provided all other
variables are held constant.
69
X5 - Other Petroleum Product Import (Excluding crude oil)
Other petroleum product imports variable X5 was significant and positive for the per
capita GDPs of the least developed countries. This outcome implies that a unit increase
in value of other petroleum products imported in the least developed countries will
result in a 0.00000012622 units increase in their per capita GDPs. In other words, for
every 1% increase in the value of other petroleum products imported, there will be a
corresponding 0.0000126% increase in the per capita GDPs of the least developed
nations.
X6 – Natural Gas Export per Capita
The insignificance of the per capita Natural Gas Export variable was observed. This
outcome suggests that there is no statistically significant relationship between the
value of natural gas exports in least developed nations and their respective GDPs.
Given the scarcity of data originating from the least developed nations, it is
conceivable that the available information may be insufficient to ascertain the
significance of natural gas exports in these countries. This indicates that the value of
LDCs' natural gas exports has no demonstrable impact on their GDP per capita. Put
differently, the value of LDCs' per capita natural gas exports is too low to have a
meaningful impact on their GDPs. X7 – Natural Gas Import per Capita
The statistical analysis revealed that the variable representing Natural Gas Import per
capita was not statistically significant in the context of the least developed nations.
This outcome suggests that there is no discernible relationship between the monetary
values of natural gas imports in Least Developed Countries (LDCs) and their per capita
Gross Domestic Product (GDP). In alternative terms, the per capita natural gas import
value of Least Developed Countries (LDCs) is insufficient to significantly influence
their per capita Gross Domestic Products (GDPs).
X8 - Total Energy Used per Capita
For the Least Developed Countries, the variable X8 pertaining to the total energy used
per capita proved to be statistically significant and positively impacts the nations' gross
domestic product (GDP). Thus, a one-unit increase in the per capita energy consumed
in Least Developed Countries (LDCs) will lead to a corresponding 0.10361 units
70
(TeraWatt Hour) rise in their Gross Domestic Product (GDP), as long as other
variables are held constant. In other words, for every 1% increase in the per capita
energy consumption in the least developed countries, there will be a corresponding
10.361% rise in their GDPs if all other variables are kept constant.
X9 - Oil Electricity per Capita
The study revealed a significant and positive relationship between the expenditure on
oil for electricity generation in the least developed countries. Consequently, a unit rise
in the per capita oil electricity generated will result in a corresponding 2.9398 units
rise in the per capita GDPs of the least developed nations. Accordingly, for every 1%
increase in oil electricity, there will be a corresponding 293.98% increase in the per
capita GDPs of the least developed countries, if all other variables are kept constant.
X10 - Gas Electricity per Capita
Gas electricity per capita variable was significant and positive towards the per capita
GDPs of the least developed countries. This result implies that each unit increase in
gas generated electricity will result in a corresponding increase in the per capita GDPs
of least developed countries by 2.2127 units. That is to say that a 1% increase in gas
electricity will result in a 221.27% increase in the per capita GDPs of least developed
countries, all the other variables kept constant.
4.4 Residual Analysis
A residual plot is a graphical representation, specifically a scatter plot, that displays
the residuals on the vertical axis and the independent variable on the horizontal axis
(Park & Dereche, 2021). It serves as a valuable tool for assessing the suitability of a
linear model in representing the provided dataset. Figure 5,6,7 represent the residual
plots for models 1,2 and 3 respectively. The shape of the residual plots show that the
datasets used for the panel regression are all suitable for linear regression analysis. The
balanced scattered data points along the zero mark on the horizontal axis indicate the
linearity of the dataset, hence the use of a linear panel model.
71
Figure 5: Residual Plot for Model 1: Developed Nations
Figure 6: Residual Plot for Model 1: Developing Nations
72
Figure 7: Residual Plot for Model 1: Least Developed Nations
Chapter 5 - Analysis And Discussion
5.1 Comparative Analysis And Discussion Of The Research Findings
This chapter unravels the economic implications of the research findings on the various
country classifications. The table below shows, at a glance, the regression results for
all categories of countries for ease of comparison.
Table 14: Comparative Table of Regression Analysis Results of Country Classifications
73
Source: Created by the authors
5.2 Energy Trade (crude oil, natural gas, and other petroleum products)
With per capita GDP representing the economic growth of countries, this section
answers the question: how does international trade of energy affect the per capita
GDPs of developed, developing, and least developed nations classifications? Our
research findings showed diverse kinds and degrees of impact of trade in energy (crude
oil and natural gas) on the per capita GDP across categories. Though the impact level
varies amongst classifications, the responses of per Capita GDP to Export and Import
dimensions of international energy trade were also observed. Thus, the analysis of the
variables: crude oil export per capita, crude oil import per capita, other petroleum
products export per capita, other petroleum products import per capita, natural gas
export per capita, and natural gas import per capita enabled us to provide answers to
this research question.
5.2.1 Impacts of Crude Oil Trade on Per Capita GDP
Comparing the behaviours of crude oil export variables across all country groups, it
was found to be significant and positive for both developed and developing countries
Comparative Table of Regression Coefficients Across Country Groups
DEVELOPED COUNTRIES
DEVELOPING COUNTRIES
LEAST DEVELOPED COUNTRIES
Variables
Parameters
P-Value
Significance
Parameters
P-Value
Significance
Parameters
P-Value
Significance
Intercept
9194.70
1.59E-12
Significant
2557.8
3.44E-32
significant
486.91
1.5571E-75
Significant
X1 (Crude Oil Production per
Capita)
-1.4175
0.066409
Not Significant
-0.0058739
0.13221
Not significant
0.001342100
0.00020596
Significant
X2 (Crude Oil Export per Capita)
0.0044839
4.12E-19
Significant
0.001104
4.07E-30
Significant
-0.000000333
0.60952
Not Significant
X3 (Crude Oil Import per Capita)
0.0088036
6.48E-10
Signifucant
-0.0003036
0.3769
Not significant
0.000010833
0.0020334
Significant
X4 (Other Petroleum Products
Export per Capita)
-0.009422
3.55E-10
Significant
-0.0006198
0.023714
Significant
-0.000012614
0.0019544
Significant
X5 (Other Petroleum Products
Import per Capita)
0.0040507
1.19E-14
Significant
0.0031679
6.53E-39
Significant
0.000001262
0.018049
Significant
X6 (Natural Gas Export per
Capita)
0.023104
1.63E-05
Significant
0.001656
4.81E-53
Significant
-0.000001702
0.60033
Not Significant
X7 (Natural Gas Import per
Capita)
-0.0017954
0.86282
Not Significant
0.030472
1.56E-26
Significant
-0.000370430
0.51176
Not Significant
X8 (Total Energy Use per Capita)
0.279
9.08E-35
Significant
0.12428
7.84E-69
Significant
0.103610000
5.1455E-78
Significant
X9 (Oil Electricity per Capita)
-1.3573
0.001129
Significant
0.57904
0.001905
Significant
2.939800000
5.4198E-34
Significant
X10 (Gas Electricity per Capita)
4.9816
7.66E-19
Significant
Variable Dropped due to
Multicolinearity
2.212700000
0.000018607
Significant
Number of Observations
962
1468
948
Error Degree of Freedom
951
1458
937
Root Mean Squared Error
16500
5880
531
R-Square
46.50%
76.90%
41.80%
R-Square Adjusted
46.00%
76.70%
41.20%
Level of Significance
5.00%
5.00%
5.00%
74
but not significant for least developed countries. It also showed that developed
countries profit more from crude oil export than developing and least developed
countries when the magnitude of impact on their respective per capita GDPs was
compared. The panel regression output revealed that for every 1% increase in crude
oil export value per annum, there will be corresponding 0.4484% and 0.1104%
increases in the per capita GDPs of developed and developing countries respectively,
provided that all other variables are kept constant. Consequently, the more developed
and developing nations increase their earnings from crude oil export trade, the more
economic growth per capita they will experience.
Related to the above is a study conducted by Osintseva (2022) in which statistical and
regression techniques were employed to validate the positive link between variations
in oil prices and economic development, emphasising the increasing impact of the
scale effect. This implies that countries with bigger absolute GDP and higher
hydrocarbon export may see more significant economic growth as a result of
favourable fluctuations in oil prices compared to smaller economies. This relates to
the positive impact of crude oil export on developed and developing countries’ per
capita GDPs on one hand and the insignificance of crude oil export on least developed
countries’ per capita GDPs on the other hand, based on the findings of our study. The
economic growth of oil-exporting countries is heavily reliant on fluctuations in oil
prices and alterations in oil production levels (Osintseva, 2022). Contrary to the
prevailing views, during economic downturns, nations do not necessarily restrict oil
exports in response to falling global oil prices, instead, there is a shift in the function
of the price component, where maintaining an income-balance strategy becomes a
crucial instrument for determining optimal production levels (Osintseva, 2022).
Furthermore, Osintseva (2022), observed that a 1% rise in oil production may
potentially lead to varying levels of GDP growth for different nations. Specifically,
the considered OPEC countries may experience a GDP growth of about 0.0367%
upwards. On the other hand, non-OPEC member countries like Russia could
potentially achieve a higher GDP growth of up to 1.559%. The above is consistent
75
with the findings of this research as all OPEC member nations are either developing
or least developed nations.
However, the experience of least developed nations is different because the crude oil
trade variable was not significant for their per capita GDP. It might be that the least
developed countries’ export levels is relatively small to have a significant impact on
their per capita GDPs. It might also be due to limited trade data received for least
developed countries as earlier highlighted in the limitations of this study in chapter
one.
There is also a school of thought on the ‘resource curse’ which posits that several
nations endowed with abundant natural resources are unable to fully capitalise on their
resource richness for economic development as well as the inadequate response of
governments in these nations in addressing the welfare requirements of their populace
(Natural Resource Governance Institute, 2015). This is a probable reason crude oil
export was insignificant for the Least Developed Countries’ per capita GDPs even
though a number of them have crude oil resources. It might as well be that the large
populations of the least developed countries relative to their crude oil export earnings
make their crude oil export trade infinitesimally small that it has no impact on their
per capita GDP, even though it might impact their Gross National Product when
considered as net export earnings. It will be noted that the population effect is one of
the reasons this study focuses on the ‘per capita values’ of all the variables.
According to the Centre on Global Energy Policy (CGEP), a major problem of the
least developed countries is their inability to convert revenues from crude oil exports
into real economic growth. This position is strengthened by the CGEP, (2019) report
which noted that throughout history, a significant portion of the discourse around
energy and emerging nations has been on the formidable task these countries have had
in effectively channeling the proceeds derived from their exports of crude oil and
natural gas into sustainable economic development. The aforementioned issue
76
continues to pose a significant difficulty for several emerging nations that rely on
energy exports.
Crude oil import on the other hand shows a significant and positive correlation for the
developed and least developed countries. It was however not significant for developing
countries. Again, the level of impact varies considerably between developed and least
developed nations. While every 1% increase in the per capita crude oil import value
per annum leads to a 0.88% increase in the per capita GDPs of developed nations, it
results in a 0.00108% per capita GDP increase for the least developed nations. The
fact that crude oil export and import are all significant and positive for developed
countries tells a lot about their involvement in international energy (oil and natural
gas) trade and consequent economic development. Their ability and capability to add
value to their crude oil further justifies the significance of crude oil import for
developed countries.
As noted by Sahoo et al. (nd), the importation of crude oil has a positive impact on
India's current account balances because India engages in the importation, refining,
and selling of petroleum products on the global market to generate foreign exchange
earnings, hence contributing to the enhancement of India's current account balances.
One further rationale provided by Sahoo et al. (nd) for the favorable influence of crude
oil imports on India's economy was the capacity to utilise the crude oil imports for
energy generation to enhance production output and bolster foreign exchange earnings
of India. Accordingly, developed countries much more engage in value addition and
crude oil utilisation for energy, hence the significant contribution of both crude oil
export and import to their economies. The significance of crude oil import in the least
developed countries suggests their reliance on oil for energy. This is corroborated by
the positive significance of oil electricity for this country category earlier highlighted
in chapter four.
The contribution of crude oil imports to the per capita GDP of least developed nations
is trivial relative to the developed nations and this may be a reflection of both their
77
energy demand and consumption and their involvement in international energy trade.
The narrow impact of crude oil imports on the economies of the least developed
countries may also be attributed to their insufficient ability to enhance the value of
crude oil, as well as the influence of price fluctuations and low levels of industrial
activity that wouldn’t generate a favourable return on investment for the economy
when compared to developed nations.
The situation for developing nations is however different. Huntington, (2015) observed
the absence of impact of crude oil importation on the current account balances of
developing nations. It was noted that a good number of oil-producing and exporting
nations fall within the developing countries category and this partly explains the
significance of crude oil export trade on their economies. Also, a good number of
developing countries cannot refine crude oil and are dependent on the importation of
refined products. This development further compounds the chances of making
economic gains from crude oil importation. Hence, the importation of crude oil in
developing nations is not an economic priority as indicated by the findings of this
study. It also suggests that they are largely self-sufficient in crude oil production and
export given that the export trade of crude oil was significant and positive for them
just as the import of petroleum products was significant and positive.
In furtherance of the discussion on energy trade across country categories, it is also
found that the export of other petroleum products variable was significant but negative
for all county categories. The negative coefficients of the Other Petroleum Products
export variable show that the more petroleum products are exported, the more the per
capita GDPs of all country categories decline, thus supporting the need to satisfy
domestic energy requirements especially for the industrial production sector. In
effect, for every 1% increase in the export of other petroleum products by developed,
developing, and least developed country groups, there are corresponding per capita
GDP declines of 0.942%. 0.06198% and 0.00126% respectively. Economically
speaking, it costs the various country categories more to export petroleum products
especially if local demand has not been sufficiently met. In effect, developed countries
78
lose more to petroleum products export, followed by the developing and the least
developed countries. It is seemingly more beneficial to use petroleum products to
satisfy domestic energy needs for production and stimulation of value-adding
economic activities than relying on revenues from petroleum product exports, which
are subject to price volatilities with possible consequent negative impacts on the per
capita GDPs. This is because not fulfilling domestic requirements entails sourcing for
energy sources externally which may impact adversely the economy.
Generally, the reliance on oil hurts the GDP per capita in the long term, hence
substantiating the resource curse argument. In the long term, there is a negative
correlation between a 10-percentage point rise in the oil export share and a 7%
decrease in GDP per capita (Kakanov et al., 2018). The study by Kakanov et al.,
(2018) also presented empirical data supporting the presence of a non-linear
relationship between oil dependency and its harmful effects on the GDP. Specifically,
as oil dependence increases, the magnitude of its negative impact on the GDP also
deepens. Therefore, all country classifications should be cautious over inordinate
reliance on crude oil and natural gas as a single means of earning foreign revenue,
rather, should focus on their use to support economic activities for development. This
study also found that there could be some connection between the negative impacts of
other petroleum product exports and the positive significance of other petroleum
products imported across all country categories. The positive impacts of other
petroleum products exports may be a consequence of the efforts by nations to satisfy
domestic energy deficits or a trade policy objective of gaining from international
commodity trade by these nations. Accordingly, for every 1% increase in the value of
other petroleum products imports by developed, developing, and least developed
nations, there are corresponding 0.405%, 0.3168%, and 0.000126% increases in their
per capita GDPs per annum respectively. The magnitude of impacts caused by the
importation of other petroleum products across the three country categories differs and
reflects their levels of energy need, energy consumption, or energy trade.
79
The findings of this study further underscore the point that nations’ economies require
energy and energy-related products to run efficiently and sustainably. Put differently,
the value derivable from domestic consumption of other petroleum products is more
than the value derivable from export of the same. That is, the opportunity cost of
exporting other petroleum products was higher than that for locally consuming them
within the three broad categories of nations.
Foreign revenues generated through increased exports enable the acquisition of capital
goods and factors of production, consequently enhancing the productive capacity of a
nation's economy (Ramos, 2001). However, most of the developing and least
developed countries may be lacking in the ability to convert export revenues to
enhance value addition to their economies as the majority of crude oil refineries in the
world are owned and situated within the developed countries.
As suggested by the findings of Sahoo et al. (nd), it may be more beneficial for the
developing and least developed countries to, like India, focus on using the available
products (produced or imported) to support industrialization and production which
may add more values to their GDPs than out rightly selling them in a volatile petroleum
products price market.
5.2.2 Impacts of Natural Gas Trade on Per Capita GDP
International trade of natural gas exhibited a very diverse behaviour towards the per
capita GDPs of the three country classifications both on the export and the import
dimensions. While the natural gas export trade was significant and positive for
developed nations, the import component was insignificant for them. For the
developing countries, both export and import trade of natural gas were significant and
positive while there was no statistically significant impact of natural gas export and
import trade on the per capita GDPs of the least developed countries. These outcomes
have implications for the energy trade of the various country groups. For instance,
every 1% increase in value per annum of natural gas export has a corresponding 2.31%
and 0.1656% increase in the per capita GDPs of the developed and developing nations
respectively. While we may consider that developed countries have attained
selfsufficiency in their domestic natural gas requirement leading to the positive
80
significance of its export trade, we note that for developing countries, this may not be
about self-sufficiency but the fact that huge natural gas deposits are found in some of
their countries, and as revealed by Ramos (2001), foreign exchange earnings from
export trade enables the acquisition of capital goods and factor inputs which
consequently supports the productive capacity of a nation's economy.
Moreover, the use of cleaner fuels such as natural gas - which releases about half of
the CO2 footprints of other fossil fuels - has been on the global agenda in recent times
as a bridge gas heralding the transition to more clean and renewable energies (World
Population Review, 2023). This is especially so within the time scope of this research,
in the wake of severe health and environmental concerns regarding carbon emissions.
Developed countries are top in the achievement of this energy transition agenda among
the three country categories. 50% of the top ten consumers of natural gas fall within
the developed countries category with the USA, Canada, Japan, Germany, and United
Kingdom ranking highest in that order (World Population Review, 2023). However,
for the developing countries, while ranking next to developed countries in the use of
natural gas as an energy source, their huge export of natural gas as an important
primary means of national revenue could be a contributing factor to the significance
of the natural gas export variable to their economies. This is because about 60% of the
top ten producers of natural gas are within the developing countries category (Pistilli,
2022).
Furthermore, the result showed clearly that Least Developed Countries are not
significantly engaged in natural gas trade as much as other country groups. We
acknowledge that several Least Developed Countries have natural gas deposits and
export the same, yet, their trade in natural gas was not sufficient to cause an effect on
their per capita GDPs at a 5% level of significance.
In all, it suffices to conclude that least developed countries have no statistically
significant and economically profitable natural gas trade and this may be connected
with the lack of capacity and know-how to produce, store, and trade on this important
but delicately volatile commodity - natural gas. Therefore, a clear strategy on gas
energy trade and utilisation by the least developed countries is imperative, if they
81
desire to profit from the gains of natural gas export like developed and developing
countries, especially the natural gas reserve-owning LDCs.
From an import perspective, natural gas import was not significant for developed and
least developed countries but was significant and positive for developing countries.
Accordingly, for every 1% increase in the value expended on natural gas import per
annum by developing countries, there is a corresponding 3.047% increase in their per
capita GDPs. With the substantial production of natural gas in developed countries -
about 40% of the top ten producers - (World Population Review, 2023), we may infer
that the amount expended by developed countries to import natural gas is not
substantial enough to cause an effect on their per capita GDP, hence its insignificant
role in the model. Another consideration is the impact of alternative energies,
especially greener and renewable energy sources which may diminish huge reliance
on natural gas importation for domestic energy generation and use (Rezai & Van Der
Ploeg, 2017). Furthermore, the volatile state of natural gas makes it difficult to store
and trade natural gas when its price improves on the international market as most
natural gas trades are from production sites to consumption locations.
On the part of developing countries, we can deduce that the positive significance of
natural gas export, as well as natural gas import trade, is an indication of their ability
to profit from their natural gas deposits for exports as well as the import of natural gas
for energy generation to support economic activities and their large populations,
especially those countries that are not endowed with natural gas deposits. Hence, by
having both export and import natural gas variables significant and positive, we can
conclude that developing countries' trade of natural gas impacted their economic
development more than developed and Least Developed Countries whose natural gas
trade within the time scope for this study did not reasonably count for their respective
economies.
For the least developed countries, the non-significance of both natural export and
import variables reveals their limited trade in natural gas. Therefore, governments of
Least Developed Countries should put in place, policies and mechanisms that support
82
trade in natural gas either by expanding their natural gas utilisation infrastructure for
energy generation (which was significant for them) or by developing adequate natural
gas capture, storage, and delivery infrastructure, especially countries that has natural
gas deposits, considering that trade in natural gas was beneficial for both developed
and developing countries in different ways. We consider that Least Developed
countries may have more to learn from developing countries than developed countries
due to the proximity or similarity of their economic circumstances to the developing
countries than to developed countries.
5.3 Impact of Energy Consumption on Per Capita GDP
In an attempt to answer the research question: how does per capita energy consumption
affect the GDPs of developed, developing, and least developed nations groups, the
behaviour of three variables (total energy use per capita, oil electricity per capita, and
gas electricity per capita) to the GDPs of the three country classifications were
considered.
This research shows that at a 5% level of significance, energy consumption was
significant and positive for all country classifications. Thus, energy use per capita
positively influences the per capita GDPs of the three broad categories of nations
considered in this study. However, herein as well the magnitude of impact varied
across the classification.
Using the panel regression parameter estimates, it is established that energy use per
capita in developed nations showed a higher impact on per capita GDP than in
developing and least developed counterparts. In effect, for every 1% increase in per
capita energy consumption (KWH) in developed countries, there is a corresponding
27.9% increase in their per capita GDP. On the other hand, per capita energy
consumption in developing countries was more impactful than in the least developed
countries. While a 1% increase in energy consumption per capita in developing
countries results in a 12.43% rise in their per capita GDP, a 1% increase in per capita
energy consumption results in a 10.36% increase in the per capita GDPs of least
developed countries.
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Hence, it can be concluded that energy use across country classifications reflects their
respective levels of industrialization and development. Developed countries have
attained a very high level of industrialization that requires huge energy consumption
to operate effectively (Beenstock & Willcocks, 1981) Countries such as the United
States of America, Germany, France, United Kingdom, Spain etc. which are huge
energy users within the developed countries group have built huge energy consuming
public infrastructures and equipment such as electric rails, electric cars besides
industries and household energy consumptions (Soytas and Sari, 2003). Although
some developed nations have resorted to offshoring some or most of their productions
processes to developing and least developed countries to leverage cheap labour,
government incentives, etc., (Koistinen & Lipartito, 2019), the result of this studies
reveals that some developed nations still retained larger shares of the global energy
consumption as noted by World Population Review, (2023). It may be inferred that
developed nations have more economically viable energy deployment than developing
and least developed nations. A long history of large-scale industrial activities, public
infrastructure, and large populations (World Population Review, 2023) as well as
heightened household energy requirements due to extreme weather conditions may
have accounted for this high level of impact of energy consumption on developed
countries’ per capita GDP.
Conversely, developing nations are known as emerging economies given the high rate
of upspring of industrial activities in those countries. Most Asian, South American,
and African countries including China, India, Brazil, and South Africa are notable for
huge industrial activities and consequent energy consumption within the developing
countries group (CGEP, 2019). Also, the prevalence of small and medium-scale
enterprises as well as large populations requiring energy at various levels of economic
engagement could account for the substantial impact of energy consumption on the
per capita GDPs of the developing nations.
The least developed nations also have significant energy requirements, especially for
their moderate industrial activities, low-level productions, small and medium-scale
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enterprises, and household energy needs considering their increasing populations. In
all, energy consumption and its impact on the per capita GDPs varies across the
country groups in proportion to their energy demands predicated mainly on their level
of industrial activities.
The findings deducted from the panel regression of the research are supported by
various earlier studies, especially in the backdrop of the ongoing debate on the
relationship between energy consumption and GDP among scholars, governments, and
researchers. While some argue that energy is an important factor input alongside other
factors of production like capital and labour, making it crucial for economic
development (Huseyin Kalyoncu et al., 2013), others hold that energy consumption is
only a small part of the GDP and does not have a significant impact on economic
growth.
In their study, Narayan and Smyth (2008) employed a multivariate panel Vector Error
Correction Model (VECM) to analyse the relationship between energy consumption
and economic growth in the G-7 nations. Their findings indicated that energy use had
a positive impact on economic development within the G-7 countries. In a similar
study conducted by Ozturk et al. (2010), panel causality was employed to examine the
relationship between economic growth and energy use across 51 countries categorised
as low-income, lower-middle-income, and upper-middle-income. The findings
revealed that in low-income countries, economic growth positively influences energy
use. In middle-income countries, a two-way causality was observed between economic
growth and energy use. However, no significant relationship between energy use and
economic development was found in upper-middle-income countries.
Apergis and Payne (2009) also employed a multivariate panel Vector Error Correction
Model (VECM) to examine the causative relationships in 11 nations belonging to the
Commonwealth of Nations. Their findings indicated the presence of a bidirectional
causation between energy consumption and economic development within these
countries.
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Masih and Masih (1996) used the Sims Causality and Granger Causality frameworks
to examine the association between economic growth and energy consumption in
several countries, namely Malaysia, Singapore, Philippines, India, Indonesia, and
Pakistan. The findings of their analysis revealed that, in the case of India and
Indonesia, energy consumption was found to have a unidirectional impact on
economic growth. Conversely, in Pakistan, the relationship between energy
consumption and economic growth was found to be bidirectional. A study by Yu and
Choi (1985) utilised the Granger Test to examine the causal relationship between
energy consumption and economic growth in several countries. They found evidence
suggesting that energy consumption leads to economic development in South Korea
and the Philippines.
Moreover, Glasure and Lee (1998) employed the Bivariate Vector Error Correction
Model (VECM) to demonstrate the presence of bidirectional causation between
economic growth and Gross Domestic Product (GDP) in South Korea and Singapore.
Similarly, Cheng (1999) demonstrated that in the context of India, there exists a
positive relationship between economic growth and energy use. Asafu-Adjaye (2000)
used the Trivariate Vector Error Correction Model (VECM), to show that energy
consumption in India and Indonesia has positive and unidirectional effects associated
with economic growth. However, in the case of Thailand and the Philippines, a
bidirectional causal relationship was seen between economic growth and energy
consumption. Similarly, Soytas and Sari (2003) employed a Bivariate Vector Error
Correction Model (VECM) to demonstrate the causal effects from economic growth
on energy usage in Turkey and South Korea. Conversely, their findings indicate that
in Argentina, Canada, the USA, and the United Kingdom, there exists a mutual impact
between energy use and economic growth. Moreover, a scholarly investigation
conducted by Lee and Lee (2010) employed a multivariate panel Vector Error
Correction Model (VECM) to demonstrate the existence of bidirectional causation
between economic development and energy consumption across 25 member nations
of the Organization for Economic Co-operation and Development (OECD). In a
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similar vein, Bekle et al. (2010) employed the Granger Causation Test to demonstrate
the presence of bidirectional causation between economic development and energy
consumption across a sample of 25 OECD nations.
5.4 Impact of Oil Electricity on Per Capita GDP
The result of the panel regression analysis showed that oil electricity and gas electricity
variables were significant across all country categories. This shows that all countries
are still largely dependent on oil and gas resources for their energy requirement.
However, while oil electricity was positively significant for developing and least
developed nations, it was negative for the developed countries. In other words, in the
developing nations and least developed nations, an increase in oil electricity increases
their per capita GDP (economic development) but at different rates with least
developed nations experiencing more impact from oil electricity than developing
nations. Accordingly, in developing nations, a 1% increase in the oil electricity per
capita will result in a 57.904% increase in their per capita GDPs while for the least
developed nations, every 1% increase in oil electricity generation results in a
corresponding 293.98% increase in the per capita GDPs of the least developed
countries, if all other variables are kept constant. However, for the developed nations,
a 1% increase in per capita oil electricity will result in a 135.75% decline in the per
capita GDPs of developed nations, as long as other variables are kept constant.
These disparities in the rate of impact between developing and least developed
countries could be attributed to several reasons. Firstly, the developing countries may
be investing in alternative clean and renewable energies more than least developed
countries. This switch could be the diminishing factor for their dependence on oil
electricity, hence its impact on their per capita GDP. On the other hand, the huge
impact of oil electricity on the economies of least developed countries suggests their
massive dependence on oil, due to their low usage of renewable energies (Ritchie et
al., 2022). UNCTAD, (2021) revealed that numerous LDCs possess substantial but
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underutilised reservoirs of renewable energy sources, such as solar energy, wind
power, geothermal energy, and biomass.
For the developed nations, the negative effect of oil electricity on their per capita GDP
may be as a result of the de-emphasis on fossil fuels which could make oil electricity
unattractive because of environmental concerns. For instance, in 2022, the European
Union generated a total of 2,641 terawatt-hours (TWH) of electricity, and about 40%
of this was derived from renewable sources (Council of the European Union, 2019).
Furthermore, possible oil energy subsidies may increase the total cost of oil electricity
vis-à-vis its economic contribution to developed nations. As reported by the
International Energy Agency (IEA), has documented an excess expenditure in the form
of oil subsidy of over USD 500 billion in the year 2022, primarily within developed
countries, aimed at diminishing energy costs, especially in Europe which accounts for
around USD 350 billion of this figure (International Energy Agency, 2023). On a
global scale, the subsidies allocated to fossil fuels amounted to $7 trillion, equivalent
to 7.1 percent of the GDP in the year 2022. This figure represents a notable rise of $2
trillion compared to the year 2020, mostly attributable to government funding to
mitigate the impact of escalating energy costs (International Monetary Fund, 2022).
However, the positive significance of crude oil export in this study is an indication that
although oil electricity negatively influences developed countries’ GDP per capita,
they profit more from trading in crude oil than using it as a major source of electricity.
This could also justify the investments of developed countries on alternative renewable
energies.
Accordingly, it can be deduced that the developed countries are deeper into
alternative/renewable energy sources and are closely followed by developing countries
before least developed countries as seen in the respective levels of impacts oil and
electricity had on their GDPs. However, with the continued global de-emphasis on
fossil energies which is dominated by oil and gas, a decrease in the trade in crude oil
is expected in the future, and this has implications for global energy trade (IEA, 2023)
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As stated by the International Energy Agency (IEA, 2023), there is an increasing
momentum in the transition towards an economy powered by clean energy. It is
anticipated that the worldwide use of oil will reach its highest point before the end of
this decade, as a result of advancements in electric cars, energy efficiency, and other
associated technologies. IEA (2023) also noted that beyond 2026, the use of oil as a
source of fuels for transportation is projected to diminish due to the increasing
prevalence of electric cars, the advancement of biofuels, and the enhancement of fuel
efficiency, all of which contribute to a reduction in oil consumption. Accordingly, it is
crucial for oil producers to closely monitor the increasing speed of change and make
informed choices regarding oil investments to facilitate a smooth transition. (IEA,
2023).
Generally, crude oil electricity generation has more impact on the economies of least
developed countries than developing countries, while it negatively affects the
developed countries’ economies.
5.4 Impact of Gas Electricity
Comparatively, gas electricity had more impact on the per capita GDPs of developed
nations than in least developed nations while it was not featured in the model for
developing nations due to multicollinearity with energy use per capita variable. The
outcome of the panel regression proved that, with a 1% increase in per capita gas
electricity in developed nations, there will be about a 498.16% increase in their per
capita GDPs whereas the same 1% increase in per capita gas electricity in least
developing nations leads to 221.27% increase in their per capita GDPs. With per capita
energy use substituting for gas electricity in developing nations, it can be inferred that
the outcome of the energy use per capita holds for gas electricity for the developing
nations for at least 80% of the time. Hence, proving its impact on GDPs across all
country groups.
Also, the magnitude of the impact of gas electricity on the economies of the developed
and least developed countries may be an indication of their various levels of
industrialization which contributes to their energy demand and consumption.
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Mashayekhi, (1988) noted that 45 percent, or 47 trillion cubic meters, of the world's
gas reserves in 1987 were located in developing nations, ten of which accounted for
around 36% of global reserves, with the LDCs accounting for 10%. Despite this, LDCs
are responsible for just 13% of global natural gas usage (Mashayekhi, 1988). A report
by Ritchie et al., (2022b) revealed also that of the top 9 consumers of fossil energy,
six (USA, Australia, Germany, EU, UK, France) are developed countries while 3
(China, South Africa, and India) are developing countries. Furthermore, the primary
source of fossil fuel utilised for power generation in Europe in 2022 was natural gas,
accounting for 19.6% of the total, with coal following closely at 15.8% (Council of
the European Union, 2019). Globally, of the 29,165TWH of electricity generated in
2022, 22% came from gas, (Statista, 2023), an amount that underscores the importance
of gas electricity to the GDPs of all the country groups.
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Chapter 6 - Summary, Policy Implications and Conclusion
6.1 Summary of the Findings
The findings of this study hold considerable Economic implications for international
energy trade for the developed, developing, and least developed nations particularly
for policy decisions and trade strategy.
From the onset, it was our objectives as follows:
a. To determine the implications of international energy trade on the economies
of developed, developing, and least developed nations.
b. To determine the implications of energy consumption on the economies of
developed, developing, and least developed nations.
Although there have been similar studies on the impact of international energy trade
as presented in the literature review in chapter two, there is no known existing
literature that focused on the three-country classification by the World Bank, thus, the
focus of this research. This research aims to evaluate the economic implications of
international energy trade (vis-à-vis crude oil and natural gas) on the economies of
developed, developing, and least developed countries which can lead towards viable
policy decisions and adjustments.
To achieve this, secondary time series data related to international energy trade (Crude
Oil and Natural gas) on some identified variables was considered, and a panel data set
up. To analyse the data set, a panel regression approach was chosen. The choice of
panel regression was based on some outstanding advantages earlier highlighted in
chapter three. To address the research questions of this study which borders on how
international energy trade impacts the economic development of nations vis-à-vis
developed, developing, and least developed nations, and how per capita energy
consumption impacts the economic development of nations vis-à-vis developed,
developing, and least developed nations, the following findings were made.
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6.1.1 International trade of energy per capita GDPs
The panel regression output was very revealing. It established that causal relationships
flowing from international energy trade to per capita GDPs of developed, developing,
and least developed nations exist. The analysis revealed diverse behaviours of per
capita GDP (as the dependent variable) to the various dimensions of international trade
of energy expressed in terms of crude oil production, crude oil export/import trade,
other petroleum export/import trade, natural gas export/import trade, the total energy
used, oil electricity as well as gas electricity as explanatory variables all expressed per
capita. All the variables were denominated in per capita to account for the relativity of
the populations of the various country groups to their GDPs for more objective
comparisons.
The panel regression output showed different behaviours of per capita GDP to
international trade of energy across the three country categories and these variations
provided answers to the research questions. It showed improvements in the economies
of developed and developing nations as they increased their crude oil export trade
earnings. Specifically, assuming that all other variables remain unchanged, a 1%
annual rise in the value of crude oil exports would lead to a 0.4484% and 0.1104%
increase in the per capita GDPs of developed and developing nations, respectively.
The export of crude oil however has an insignificant effect on the GDP per capita of
the least developed countries.
The study also revealed that the developed and least developed nations both benefited
significantly and favourably from increased per capita crude oil importation. Again,
the influence differs greatly across the developed and the least developed countries.
For the developed countries, a 1% annual rise in the value of crude oil imported per
capita corresponds to a 0.88% annual increase in GDP per capita, whereas for the least
developed countries, the same factor leads to a 0.00108% increase in GDP per capita.
However, the per capita crude oil importation had no significant impact on the per
capita GDPs of the developing nations.
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Furthermore, it was observed that the export of other petroleum products exhibited
significant but negative trends across all country categories. This observation indicates
a negative association between the exportation of petroleum products and the per
capita GDPs across all nation categories. The findings indicate that a 1% rise in the
export of other petroleum products by developed, developing, and least developed
nation groups leads to a commensurate decrease of 0.942%, 0.06198%, and 0.00126%
in per capita GDP respectively. Put simply, from the perspectives of overarching
international trade and economic benefits to nations, it costs more to export other
petroleum products than import, hence underscores the importance of fulfilling
domestic energy needs for improved economic activities and per capita GDP growth
across all three nations categories.
In the same vein, it is observed that there may exist a correlation between the negative
effects of exporting other petroleum products in various country groups and the
positive impacts of importing other petroleum products in all nations groups. Thus,
this research considers import trade important in addressing the deficit in local
petroleum products requirements. Consequently, it can be shown that a 1% rise in the
value of various petroleum products imported by developed, developing, and least
developed nations is associated with respective annual increases of 0.405%, 0.3168%,
and 0.000126% in their per capita GDPs. The varying magnitude of impacts of other
petroleum products on their respective GDPs may be a reflection of the energy
requirement, consumption, and trade across the three broad nations groups.
The international trade of natural gas showed significant variation about the per capita
GDPs of the three country groups, both in terms of exports and imports. Although the
export trade of natural gas had a significant and positive impact on developed nations,
the import aspect of this trade was insignificant for the developed country
classifications. Conversely, in developing nations, the export and import trade of
natural gas held significant and positive impacts on their per capita GDPs. However,
the natural gas export and import trade had no statistically significant effect on the per
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capita GDPs of the least developed countries. The findings indicate that a rise of 1%
in the annual value of natural gas exports is associated with a concurrent increase of
2.31% in the per capita GDP of developed countries and a 0.1656% increase in the per
capita GDP of developing nations.
From an import standpoint, it can be observed that natural gas did not have
considerable importance for both developed and least developed nations. However, it
did exhibit a large and favourable impact on emerging countries. Consequently, it can
be observed that developing nations experience a 3.047% rise in their per capita GDPs
for each 1% increment in the expenditure allocated to natural gas imports on an annual
basis. For developing nations, it can be inferred that the favourable implications of
both natural gas exports and imports signify their capacity to capitalise on their natural
gas reserves to export and import natural gas, respectively. This serves to facilitate
energy generation for supporting economic endeavours.
The lack of significance in both the natural gas export and import variables for the
least developed nations indicates their minimal involvement in natural gas trading.
Hence, the governments of Least Developed Countries (LDCs) must implement
policies and mechanisms that facilitate the trade of natural gas. This can be achieved
through the expansion of their existing natural gas utilisation infrastructure for more
energy generation, or by developing appropriate infrastructure for the capture, storage,
and delivery of natural gas subsequently leading to economic growth. Countries with
significant gas deposits need to prioritise such initiatives.
6.1.2 Energy consumption per capita GDPs
The demand, supply, and consumption of energy through manufacturing, electricity,
transportation, cooking, and heating constitute the major drivers of international
energy trade (Teba, 2018). The panel regression parameter estimates showed that the
influence of energy usage per capita on per capita GDP is more pronounced in
developed nations compared to developing and least developed nations. In essence, it
can be shown that a rise of 1% in per capita energy consumption (KWH) in
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industrialised nations is associated with a proportional increase of 27.9% in their per
capita GDP. Conversely, the per capita energy consumption of emerging nations had
a greater influence on their per capita GDP compared to the least developed countries.
The findings indicate that a 1% increase in energy consumption per capita in
developing nations is associated with a corresponding 12.43% increase in their per
capita GDP. Similarly, a 1% increase in per capita energy consumption is associated
with a 10.36% increase in the per capita GDPs of least developed countries.
The findings from the panel regression analysis indicate that both the oil electricity
and gas electricity variables exhibit statistical significance across all nation categories.
However, whereas oil electricity had a significant and positive impact on the
development of both developing and least developed nations, it had a negative effect
on developed countries. In the context of developing and least developed nations, it
can be observed that an increase in oil-generated electricity has a varying effect on
their per capita GDPs. Specifically, Least Developed Countries tend to have a more
pronounced influence from the utilisation of oil-generated electricity compared to
developing nations.
In the context of developing nations, a 1% increase in per capita oil electricity
expenditure is associated with a substantial 57.904% increase in per capita GDP.
Similarly, for the least developed nations, a 1% increase in oil electricity expenditure
corresponds to a significant 293.98% increase in per capita GDP, assuming all other
variables remain constant. In the context of developed countries, it can be shown that
a 1% rise in per capita oil electricity generation and consumption leads to a substantial
loss of 135.75% in the per capita GDPs of these nations, assuming all other factors
remain constant.
In developed nations, the adverse impact of oil-generated electricity on per capita GDP
can be attributed to the reduced emphasis on fossil fuels, rendering oil-based electricity
less appealing in these countries, particularly due to concerns about sustainability and
the environment. Moreover, it is worth noting that possible subsidies for oil energy
might potentially lead to an escalation in the overall expenses associated with
oilgenerated power, relative to its economic impact on developed countries.
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In a comparative analysis, it was shown that the influence of gas electricity on the per
capita GDPs of developed nations was more significant than in least developed
nations. However, it was not included in the model for developing nations due to
multicollinearity issues with the energy usage per capita variable.
The results of the panel regression analysis indicate that a 1% increase in per capita
gas electricity in developed nations is associated with an approximately 498.16%
increase in their per capita GDPs. Conversely, a similar 1% increase in per capita gas
electricity in the least developing nations is associated with a 221.27% increase in their
per capita GDPs.
By replacing per capita energy usage for gas electricity in developing nations, it may
be inferred that the findings about energy consumption per capita apply to gas
electricity in developing nations at least 80% of the time. Therefore, the utilisation of
natural gas for power generation could be said to have had a significant influence on
the per capita Gross Domestic product (GDPs) of all categories of countries.
6.2 Establishing Trade Patterns
It is vital to establish the predominant trade patterns among the various classifications
in determining the impact of international energy trade on their respective economies.
6.2.1. The Developed Nations
The per capita GDPs of developed nations reacted significantly to both positive and
negative changes in energy trade. While crude oil and natural gas export trades
positively influenced the per capita GDPs, only other petroleum products export trade
variable was negative on the per capita GDPs. From the import perspective, crude oil
imports and other petroleum products import variables were positive for the per capita
GDPs of the developed nations while natural gas import was insignificant.
Therefore, in terms of energy trade impacts on the per capita GDPs of developed
countries, we can see that both the export and import trade of energy made a substantial
impact on the economic development of developed nations. Thus, it is imperative that
developed nations focus on both import and export trade policies with special attention
on other petroleum products import variables which had negative effects on the per
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capita GDP, as well as the natural gas import which had no significant effect on the
GDP.
6.2.2 Developing Nations
Developing nations share similar trade patterns with developed nations but to different
degrees. Both export and import energy trade influenced the per capita GDPs of
developing nations. While crude oil and natural gas export trade variables had positive
influences, other petroleum products export variables had a negative impact on the per
capita GDPs of developing nations. From an import perspective, both other petroleum
products and natural gas import trade variables had positive influences on the per
capita GDPs of developing nations. However, the crude oil import trade variable was
of no statistical significance.
Accordingly, developing nations should seek to sustain and improve their energy
export and import trade but closely monitor and reengineer their crude oil import trade
for positive contribution to economic development and this could be achieved through
strategic value-adding activities such as crude refining or effective and profitable crude
oil commodity trade.
6.2.3 Least Developed Nations
Energy trade pattern in the least developed nations was entirely different. Export trade
variables such as crude oil and natural gas were not significant towards the per capita
GDPs of LDCs. Notably, the only significant export trade variable (other petroleum
products export) had a negative impact on the per capita GDPs of the least developed
nations. Nevertheless, the import trade of energy was mostly significant and positive
for the least developed nations. Crude oil and other petroleum products imports were
significant and positive on the per capita GDPs while natural gas import was not
statistically significant. Hence, developed countries could be said to be
importdependent on energy trade.
6.3 Implications Of The Findings For Policy Making
International energy trade calls for continuous and comprehensive policy reviews that
encompass several aspects of energy trade. The findings of this study afford
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policymakers the latitude to model the probable consequences of policy modifications,
hence facilitating more informed decision-making about their countries’ trade of
energy (Greene, 2002). Accordingly, governments need to reassess their strategic
priorities, encompassing a range of actions such as reformulating energy policy,
diversifying economic revenue streams, and making adjustments to diplomatic
relationships, especially for developing and least developed nations.
It is of utmost importance to consider and monitor the implications of fluctuations in
crude oil and natural gas trade on the economic or social development of a nation
(Battistin & Bertoni, 2023). The implementation of a policy adjustment or a sudden
fluctuation in Crude oil or Natural Gas prices may not provide immediate
consequences but rather exhibit themselves gradually over an extended period,
spanning months or even years. Policymakers have the opportunity to customise
actions that specifically address those concerns (Cameron & Trivedi, 2005)
subsequently leading to positive economic implications. Policymakers can predict and
make preparations for future consequences by drawing insights from previous
occurrences (Wooldridge, 2010). The possibility for fiscal and monetary policy
modifications arises when governments shift their focus away from oil and gas
earnings, hence potentially resulting in transformations in economic policies. In
contrast, the environmental agenda may have a greater inclination towards the
promotion of green energy and the implementation of sustainable rules (Angrist &
Pischke, 2009). Policymakers have the opportunity to use knowledge of the diverse
effects of trade across different countries to facilitate coordinated multinational
actions, like the establishment of trade agreements or the creation of shared reserves
(Arellano, 2003).
The strategic imperatives of states may undergo adjustments, with a heightened focus
on ensuring the security of supply lines and the possibility of altering defense postures.
The prioritisation of research and development, particularly on sustainable energy
security is expected to play a crucial role in driving future economic expansion thus
attracting foreign investments through a favourable and competitive business
environment. To effectively mitigate and navigate the fragile and evolving global
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energy trade, it is imperative for governments to focus on areas of comparative
advantage, adaptability, and sustainability. Stakeholders' engagement will as well play
a pivotal role in managing public expectations and facilitating a seamless transition
among the various changes taking place. Policymakers will encounter a critical
juncture, necessitating adaptability, strategic planning, and cooperative efforts to
effectively navigate their respective countries among the complex circumstances of
global energy trade.
Following from the findings of this study, the following suggestions may apply to
various nations within the three broad categories considered in this study.
i. As noted by Bashiri Behmiri and Pires Manso (2013), since energy
consumption is positively linked with economic development across all
country categories, reductions in energy supply and consumption should be
avoided, given its detrimental impact on the economic prospects of nations.
Accordingly, national policies on energy should encompass a steady and
competitive energy supply to a nation, especially for value-adding economic
activities such as transportation and industrial production. Where inevitable,
energy subsidies may be administered, such that the overall cost of energy
should not offset the resulting economic benefits to the nations.
ii. Considering the negative effects of other petroleum products exported across
all country groups, policymakers within these nations should cautiously
navigate their energy policies away from an inordinate reliance on petroleum
products as just a single means of earning foreign revenues, rather, they should
also optimise their use to primarily support domestic economic activities for
development.
iii. For the least developed countries, the non-significance of both natural gas
export and import variables revealed their limited involvement in the natural
gas trade. Therefore, a clear strategy for natural gas energy trade and utilisation
by the least developed countries is imperative. Hence, governments of Least
Developed Countries could put in place policies and mechanisms that support
the trade of natural gas either by expanding natural gas utilisation
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infrastructure for energy generation (which was significant for them) or by
developing adequate natural gas capture, storage, and delivery infrastructure,
particularly nations that have natural gas deposits. This is imperative given that
natural gas trade was beneficial for both developed and developing countries.
Additionally, developed and developing nations could put strategies in place
to sustain their gains from natural gas trade, especially by keeping a tab on the
trade volatilities that could introduce negative influences on their natural gas
export and import trade.
iv. Sequel to the projections of the International Energy Agency, beyond 2026,
the use of oil as a source of fuels for transportation is projected to diminish due
to the increasing prevalence of electric cars, the advancement of biofuels, and
the enhancement of fuel efficiency, all of which contribute to a reduction in oil
consumption, it is crucial for oil and gas dependent economies to closely
monitor the increasing speed of change and make informed choices regarding
oil investments to facilitate a smooth transition to cleaner fuels (IEA, 2023).
Besides the projections of the IEA, the conflict in Ukraine exemplifies the
substantial influence of political events on the energy supply chain and
sustainability. In the same vein, the year 2020 witnessed a similar occurrence
when the global pandemic of Covid-19 emerged. The global consumption of
power experienced a significant decline as several countries implemented
lockdown measures (IEA, 2022), developing and least developed economies
that are solely dependent on oil revenues should take cogent steps to diversify
their national revenue bases to forestall extreme shocks that may arise due to
pandemic or geopolitical tensions that could hamper their international energy
trade and economic stability.
6.5 Conclusion
Energy Trade in Developed and developing nations focuses on both the export and
import of energy commodities. This has significant influences on their respective per
capita GDPs. However, from the findings of this research, the magnitude of impact is
higher in developed nations than in developing nations. Conversely, the least
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developed nations are mainly import concentrated in international energy trade, a
situation that suggests a lack of requisite capacity to produce, utilise, or export energy
on significant commercial scales. Most of the energy trade variables were too
insignificant to have a substantial effect on their per capita GDPs and this is revealed
on the level of energy demand, utilisation, and trade in the least developed nations.
Energy use showed significant and positive across all country Classifications with
developed nations having more impact on per capita GDP from per capita energy use
than developing and least developed nations respectively. On oil electricity, the least
developed nations exhibited the highest level of impact followed by the developing
nations, while developed nations showed a negative effect of oil electricity on per
capita GDP. It is our considered thought that the negative influence of oil electricity
in developed nations signals a move away from oil electricity in these nations whereas
developing and least developed still highly depend on oil electricity. While we
acknowledge that energy sustainability and environmental concerns could account for
the negative effect of oil electricity in developed nations, it is notable that the concept
of energy sustainability is not as pronounced in the developing and least developed
nations, hence, their huge dependence on oil electricity and its impact on their per
capita GDPs.
Gas electricity, on the other hand, showed the highest impact on the per capita GDPs
of the developed and least developed nations. However, the magnitude of the impact
of gas electricity on the per capita GDPs of the developing nations could not be
ascertained due to its multicollinearity with per capita energy use.
In all, international energy trade across country classifications impacts their
economies. However, enhancing the capabilities of governments, administrations, and
economic management, together with promoting openness and accountability, which
play a crucial role in facilitating inclusive development outcomes are imperative for
improving the benefits derived from international energy trade. All three country
classifications could consider policies that capture the future direction of global energy
sources in respect of a possible decline in oil dependence and the promotion of
renewable fuels for the future, especially in developing and least developed nations.
